NAMIC Wiki - User contributions [en]

Projects:RegistrationDocumentation:UseCaseInventory

2015-01-28T17:14:12Z

Meier:

Back to [[Projects:ARRASuplements|ARRA main page]], [[Projects:RegistrationDocumentation|Registration main page]]

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<br>
<big>
'''Note: the pages below were constructed during the ARRA project cycle and are no longer actively maintained. <br>
[http://wiki.slicer.org/slicerWiki/index.php/Documentation/Nightly/Registration/RegistrationLibrary The Registration library is still maintained but has moved here]'''
</big>
<br>
<br>

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= The Slicer Registration Case Library =

{| style="color:#000000; background-color:#aaaaaa;" cellpadding="10" cellspacing="0" border="0"
|Welcome to the 3DSlicer Registration Case Library. This page is under continuous development as we add and refine case examples of image registration within 3DSlicer. The goal is for you to find here a case similar enough to your particular image registration problem to provide you with registration parameters, strategies and tutorials. The library is growing by virtue of '''user contributions'''; if you have an interesting case please consider our ''Call for Datasets'' on the right. Successful registration strategies; algorithm choice and parameters vary greatly for different image contrast and content. Each listed case comprises a test dataset to try yourself, a guided step-by-step '''tutorial''' that will show you how to register the case with 3DSlicer, the solution transform so you can compare, and a custom ''Registration Parameter Presets'' file with optimized registration parameters that you can load directly into slicer.
|
|[[Image:SlicerRegistrationLibrary_Ad.png|right|300px|link=Projects:RegistrationDocumentation:UseCaseAdvertisement|Slicer Registration Case Library: Call for Example Datasets]] <br>
[[Projects:RegistrationDocumentation:UseCaseAdvertisement|'''Consider adding your case to the library''']]
|}

*Library organized by structure below. [[Projects:RegistrationDocumentation:RegLibTable|'''Library as sortable table see here.''']]
*See here for detailed [http://www.slicer.org/slicerWiki/index.php/Slicer-3-6-FAQ '''Registration FAQ''']

== BRAIN ==

{| cellpadding="6" cellspacing="2"
|align="center" |[[Image:Registration_HLogo_IntraMRI.png| 135px |link=Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraMRI]]
|align="center" |[[Image:Registration_HLogo_IntraDTI.png| 135px |link=Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraDTI]]
|align="center" |[[Image:Registration_HLogo_IntrafMRI.png| 135px |link=Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraFMRI]]
|align="center" |[[Image:Registration_HLogo_IntraPET.png| 135px |link=Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraPETCT]]
|-
|The [[Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraMRI|'''Same Subject Brain MRI''' ]] collection contains '''structural'''MRI of the same subject, e.g. aligning follow-up to baseline or a T1w and a PDw image.
|The [[Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraDTI|'''Same Subject DTI''' ]] collection contains cases of registering a DTI dataset with an anatomical reference, such as a high-resolution MRI.
|The [[Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraFMRI|'''Same Subject fMRI''' ]] collection contains cases of registering a fMRI dataset with an anatomical reference, such as a high-resolution MRI.
|The [[Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraPETCT|'''Same Subject PET/CT/MRI''' ]] collection contains cases of registering a PET or CT dataset with an MRI or CT.
|-
|align="center" |[[Image:Registration_HLogo_InterMRI.png| 135px |link= Projects:RegistrationDocumentation:UseCaseInventory:BrainInterMRI]]
|align="center" |[[Image:Registration_HLogo_InterPET.png‎| 135px |link= Projects:RegistrationDocumentation:UseCaseInventory:BrainInterPETCT]]
|align="center" |[[Image:Registration_HLogo_Atlas.png| 135px |link= Projects:RegistrationDocumentation:UseCaseInventory:BrainAtlas]]
|
|-
|The [[Projects:RegistrationDocumentation:UseCaseInventory:BrainInterMRI|'''Different Subject Brain MRI''' ]] collection contains cases of co-registering MRI of (many) different subjects into a common space. This often includes non-rigid registration (image warping).
|The [[Projects:RegistrationDocumentation:UseCaseInventory:BrainInterPETCT|'''Different Subject PET/CT''' ]] collection contains cases of registering PET/SPECT/CT images from different subjects, e.g. aligning a SPECT perfusion atlas with an MRI.
|The [[Projects:RegistrationDocumentation:UseCaseInventory:BrainAtlas|'''Different Subject Brain Atlas''' ]] collection contains cases of registering an atlas to a single subject or building atlases from a collection of subjects.
|
|}

== OTHER ==

{| cellpadding="6" cellspacing="2"
|align="center" |[[Image:Registration_HLogo_Abdominal.png| 135px |link= Projects:RegistrationDocumentation:UseCaseInventory:Abdominal]]
|align="center" |[[Image:Registration_HLogo_Knee.png| 135px |link= Projects:RegistrationDocumentation:UseCaseInventory:Musculoskeletal]]
|align="center" |[[Image:Registration_HLogo_WholeBody.png| 135px |link= Projects:RegistrationDocumentation:UseCaseInventory:WholeBody]]
|align="center" |[[Image:Registration_HLogo_Animal.png| 135px |link= Projects:RegistrationDocumentation:UseCaseInventory:Animal]]
|-
|The [[Projects:RegistrationDocumentation:UseCaseInventory:Abdominal|'''Abdominal/Thoracic''' ]] collection contains cases of breast and abdominal MRI/CT/PET, e.g. for therapeutic assessment or interventional guidance.
|The [[Projects:RegistrationDocumentation:UseCaseInventory:Musculoskeletal|'''Musculoskeletal''' ]] collection contains cases of aligning musculoskeletal images, e.g. aligning knee MRI images.
|The [[Projects:RegistrationDocumentation:UseCaseInventory:WholeBody|'''Whole Body PET/CT''' ]] collection contains cases of registering different modalities of whole body imaging.
|The [[Projects:RegistrationDocumentation:UseCaseInventory:Animal|'''Animal MRI/CT''' ]] collection contains cases of aligning animal datasets.
|-
|align="center" |[[Image:Registration_HLogo_Auxiliary.png| 135px |link= Projects:RegistrationDocumentation:UseCaseInventory:Auxiliary]]
|-
|The [[Projects:RegistrationDocumentation:UseCaseInventory:Auxiliary|'''Auxiliary''']] collection contains images & data that can be useful for performing, visualizing or validating registration.
|}

== How to get started ==
*1. browse/search the library for a case similar to yours. The library is organized by organ (brain vs. non-brain), modality (MR, CT, PET), intra- vs. inter-subject). Each case also has a list of keywords, so you may try a direct search for a case matching yours. Or for all cases in a [[Projects:RegistrationDocumentation:RegLibTable|'''single sortable table see here.''']]
*2. If you find a good match, continue with 3. below. If you cannot find a good match, consider our [[Projects:RegistrationDocumentation:UseCaseAdvertisement|'''Call for Datasets & Registration Service''']].
*3. from the case description page, follow the links to download the data, preset file and tutorials.
*4. run the tutorial on your machine with your installation of slicer (v3.6 or higher recommended)
*5. load the preset file and try those settings on your own data
*5. if you do not get a satisfactory registration results with the presets, have a look at the ''Registration Challenges'' and ''Key Strategies'' section on the download page of your case. You will find recommendations there on how to venture forth. Try the recommended adjustments.
*6. if still unsuccessful you may have a case of interest to the library. [[Projects:RegistrationDocumentation:UseCaseAdvertisement|'''Consider adding your case to the library for a free registration''']]. Also consider posting a message to the [http://www.slicer.org/pages/Mailinglist slicer user group].
*7. if successful we'd also love to hear: [[Projects:RegistrationDocumentation:UseCaseAdvertisement|''' We gladly add your case with full acknowledgment to the library''']].

== Source & Format ==
Data is collected from a variety of sources. Most we hope to originate from user contributions. Because we want to focus on the registration problem and not be distracted by image format or other data management issues, the datasets listed here are reformatted as NRRD files. Cases under construction may be listed, and when complete a download link is added.
*[[Projects:RegistrationDocumentation:UseCaseAdvertisement|'''Call for Datasets''']]
*[[Projects:RegistrationDocumentation:RegLibList|Full List of Registration Library Cases]]
*[[Projects:RegistrationDocumentation:RegLibTable|Sortable Table of Library Cases]]
*[[Projects:RegistrationDocumentation:RegLibDataList|List of downloadable Registration Library data files]]
* All image data is anonymized, i.e. there is no identifying or patient specific information in any of the posted data. We do not keep identifiers, so we cannot retrace.
*[[Projects:RegistrationDocumentation:ParameterPresetsTutorial|How to Load/Save Registration Parameter Presets]]
*Links here also from the [[Data|NA-MIC resource page]].To be updated when moving.
*For a list/overview of registration options '''by method''' see [http://www.slicer.org/slicerWiki/index.php/Slicer3:Registration#Registration_in_3D_Slicer the '''3DSlicer Registration Portal Page''']
[[Category:Registration]]

2014 Project Week Breakout Session: Slicer for users

2014-06-25T13:45:40Z

Meier:

[[2014_Summer_Project_Week|Back to project week]]

Wednesday, 11-12

This will be an informal discussion of new features in 3D Slicer. Some of the extensions will be mentioned as well.

*Improved handling of transforms including non-rigid (Alex Yarmakovic)
*Data Store
**Registration library (Dominik Meier)
***<small>brief overview over the Data Store access to the Registration Library ([http://slicer.kitware.com/midas3/slicerdatastore/view?itemId=142765 Example Case])
***example case, link to tutorial pages, screencasts, FAQ
***new support for nonlinear transforms and transform visualization ([http://wiki.slicer.org/slicerWiki/index.php/Documentation:Nightly:Registration:RegistrationLibrary:RegLib_C12a Demo Dataset])</small>
**Tutorial data sets
*Extensions:
**Slicer RT, subject hierarchies and multi-objects - Csaba Pinter (slides: [http://www.na-mic.org/Wiki/images/8/85/Pinter_NAMIC2014Jun_SlicerRt_User.pptx pptx] [http://www.na-mic.org/Wiki/images/6/6e/Pinter_NAMIC2014Jun_SlicerRt_User.pdf pdf])
**IASEM ( Ion-Abrasion Scanning Electron Microscopy ) - Bradley Lowekamp
*** Data: http://placid.nlm.nih.gov/folder/286
**Carrera - Ivan Kolesov
**TCIABrowser - Alireza Mehrtash

2014 Project Week Breakout Session: Slicer for users

2014-06-25T13:44:50Z

Meier:

[[2014_Summer_Project_Week|Back to project week]]

Wednesday, 11-12

This will be an informal discussion of new features in 3D Slicer. Some of the extensions will be mentioned as well.

*Improved handling of transforms including non-rigid (Alex Yarmakovic)
*Data Store
**Registration library (Dominik Meier)
***<small>brief overview over the Data Store access to the Registration Library
***example case, link to tutorial pages, screencasts, FAQ
***new support for nonlinear transforms and transform visualization ([http://wiki.slicer.org/slicerWiki/index.php/Documentation:Nightly:Registration:RegistrationLibrary:RegLib_C12a Demo Dataset])</small>
**Tutorial data sets
*Extensions:
**Slicer RT, subject hierarchies and multi-objects - Csaba Pinter (slides: [http://www.na-mic.org/Wiki/images/8/85/Pinter_NAMIC2014Jun_SlicerRt_User.pptx pptx] [http://www.na-mic.org/Wiki/images/6/6e/Pinter_NAMIC2014Jun_SlicerRt_User.pdf pdf])
**IASEM ( Ion-Abrasion Scanning Electron Microscopy ) - Bradley Lowekamp
*** Data: http://placid.nlm.nih.gov/folder/286
**Carrera - Ivan Kolesov
**TCIABrowser - Alireza Mehrtash

2014 Project Week Breakout Session: Slicer for users

2014-06-25T13:44:33Z

Meier:

[[2014_Summer_Project_Week|Back to project week]]

Wednesday, 11-12

This will be an informal discussion of new features in 3D Slicer. Some of the extensions will be mentioned as well.

*Improved handling of transforms including non-rigid (Alex Yarmakovic)
*Data Store
**Registration library (Dominik Meier)
***<small>brief overview over the Data Store access to the Registration Library
***example case, link to tutorial pages, screencasts, FAQ
***new support for nonlinear transforms and transform visualization ([http://wiki.slicer.org/slicerWiki/index.php/Documentation:Nightly:Registration:RegistrationLibrary:RegLib_C12a Demo Dataset] </small>
**Tutorial data sets
*Extensions:
**Slicer RT, subject hierarchies and multi-objects - Csaba Pinter (slides: [http://www.na-mic.org/Wiki/images/8/85/Pinter_NAMIC2014Jun_SlicerRt_User.pptx pptx] [http://www.na-mic.org/Wiki/images/6/6e/Pinter_NAMIC2014Jun_SlicerRt_User.pdf pdf])
**IASEM ( Ion-Abrasion Scanning Electron Microscopy ) - Bradley Lowekamp
*** Data: http://placid.nlm.nih.gov/folder/286
**Carrera - Ivan Kolesov
**TCIABrowser - Alireza Mehrtash

2014 Project Week Breakout Session: Slicer for users

2014-06-25T13:44:16Z

Meier:

[[2014_Summer_Project_Week|Back to project week]]

Wednesday, 11-12

This will be an informal discussion of new features in 3D Slicer. Some of the extensions will be mentioned as well.

*Improved handling of transforms including non-rigid (Alex Yarmakovic)
*Data Store
**Registration library (Dominik Meier)
***<small>brief overview over the Data Store access to the Registration Library
***example case, link to tutorial pages, screencasts, FAQ
***new support for nonlinear transforms and transform visualization ([http://wiki.slicer.org/slicerWiki/index.php/Documentation:Nightly:Registration:RegistrationLibrary:RegLib_C12a] Demo Dataset</small>
**Tutorial data sets
*Extensions:
**Slicer RT, subject hierarchies and multi-objects - Csaba Pinter (slides: [http://www.na-mic.org/Wiki/images/8/85/Pinter_NAMIC2014Jun_SlicerRt_User.pptx pptx] [http://www.na-mic.org/Wiki/images/6/6e/Pinter_NAMIC2014Jun_SlicerRt_User.pdf pdf])
**IASEM ( Ion-Abrasion Scanning Electron Microscopy ) - Bradley Lowekamp
*** Data: http://placid.nlm.nih.gov/folder/286
**Carrera - Ivan Kolesov
**TCIABrowser - Alireza Mehrtash

2014 Project Week Breakout Session: Slicer for users

2014-06-24T18:49:52Z

Meier:

[[2014_Summer_Project_Week|Back to project week]]

Wednesday, 11-12

This will be an informal discussion of new features in 3D Slicer. Some of the extensions will be mentioned as well.

*Data Store
**Registration library (Dominik Meier)
***<small>brief overview over the Data Store access to the Registration Library
***example case, link to tutorial pages, screencasts, FAQ
***new support for nonlinear transforms and transform visualization</small>
**Tutorial data sets
*Extensions:
**Slicer RT
**IASEM - Bradley Lowekamp
**Carrera - Ivan Kolesov
**TCIA - Andrey Fedorov

2014 Project Week Breakout Session: Slicer for users

2014-06-24T18:47:34Z

Meier:

[[2014_Summer_Project_Week|Back to project week]]

Wednesday, 11-12

This will be an informal discussion of new features in 3D Slicer. Some of the extensions will be mentioned as well.

*Data Store
**Registration library (Dominik Meier)
***<small>brief overview over the Data Store access to the Registration Library
***example case, link to tutorial pages, screencasts
***new support for nonlinear transforms and transform visualization</small>
**Tutorial data sets
*Extensions:
**Slicer RT
**IASEM - Bradley Lowekamp
**Carrera - Ivan Kolesov
**TCIA - Andrey Fedorov

Projects:RegistrationLibrary:RegLib C16

2013-08-20T15:49:34Z

Meier:

Projects:RegistrationLibrary:RegLib C29

2013-05-09T19:54:55Z

Meier: /* Registration Results */

[[Projects:ARRASuplements|Back to ARRA main page]] <br>
[[Projects:RegistrationDocumentation|Back to Registration main page]] <br>
[[Projects:RegistrationDocumentation:UseCaseInventory|Back to Registration Use-case Inventory]] <br>

= <small>updated for '''v4.1'''</small> [[Image:Slicer4_RegLibLogo.png|150px]] <br> Slicer Registration Library Case #29: Intra-subject Brain DTI =
=== Input ===
{| style="color:#bbbbbb; " cellpadding="10" cellspacing="0" border="0"
|[[Image:RegLib_C29_thumb1.png|150px|lleft|this is the fixed reference image. All images are aligned into this space]]
|[[Image:RegArrow_Affine.png|100px|lleft]]
|[[Image:RegLib_C29_thumb2.png|150px|lleft|this is the T2 reference image, serves as target to the DTI baseline, but is itself aligned to the SPGR]]
|[[Image:RegArrow_NonRigid.png|100px|lleft]]
|[[Image:RegLib_C29_thumb3.png|150px|lleft|this is the DTI Baseline scan, to be registered with the T2]]
|[[Image:RegLib_C29_thumb4.png|150px|lleft|this is the DTI tensor image, in the same orientation as the DTI Baseline]]
|-
|fixed image/target<br>T1 SPGR
|
|moving image 1<br>T2
|
|moving image 2a<br>DTI baseline
|moving image 2b<br>DTI tensor
|}

=== Slicer4 Modules used ===
* [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/DiffusionTensorEstimation Diffusion Tensor Estimation module]
* [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS) module]
* [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/ResampleDTI Resample DTI Volume module]

===Objective / Background ===
This is a classic case of a multi-sequence MRI exam we wish to spatially align to the anatomical reference scan (T1-SPGR). The scan of interest is the DTI image to be aligned for surgical planning/reference.

=== Download ===
*DATA
**[[Media:RegLib_C29_Data.zip‎|'''Registration Library Case 29 '''<small> (Data & Solution Xforms, incl. DTI + DWI + resampled DTI, zip file 160 MB) </small>]]

*TUTORIALS (note the tutorials are for '''Slicer version 3.6'''; for [http://na-mic.org/Wiki/index.php/Projects:RegistrationLibrary:RegLib_C29#Procedures Slicer4 use the step-by-step instructions below]):
**[[Media:RegLib_C29_DTI.ppt| Powerpoint Tutorial (.ppt PowerPoint file, 1.5 MB)]]
**[[Media:RegLib_C29_DTI.pdf| Powerpoint Tutorial as PDF (PDF file 2.1 MB)]]

=== Keywords ===
MRI, brain, head, intra-subject, DTI, T1, T2, non-rigid, tumor, surgical planning

===Input Data===
*reference/fixed : T1 SPGR , 0.5x0.5x1 mm voxel size, 512 x 512 x 176
*moving 1: T2 0.5x0.5x1.5 mm voxel size, 512 x 512 x 92
*moving 2a: DTI baseline: 1 x 1 x 3 mm, 256 x 256 x 41
*moving 2b: 1 x 1 x 3 mm, 256 x 256 x 41 x 9 (tensor), original: DWI 256 x 256 x 41 x 32 directions

===Registration Challenges===
*The DWI sequence (EPI) contains strong distortions we seek to correct via non-rigid alignment
*The DWI sequence also contains strong intensity inhomogeneity (coil bias)
*the DTI baseline is similar in contrast to a T2, albeit at much lower resolution
*we have different amounts of voxel-anisotropy
*a direct registration of the DTI_baseline to the SPGR will fail, hence a 2-step approach is required

===Key Strategies===
*'''Slicer 4 recommended modules: [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BrainsFit]
*to align the DTI with the T1 we need 2 registration steps: 1.align the T2 with the T1 and 2. align the DTI with the T2. The DTI baseline scan has contrast most similar to the T2 and hence is best registered against the T2. However the structural reference scan with highest resolution and tissue contrast is the T1.
*we therefore use the following approach: 1) we first co-register the T2 with the SPGR T1. 2) we register the DTI baseline to the registered/resampled T2; 3) resample the DTI volume with the new transform
*the DTI-T2 registration includes non-rigid deformation to correct for the strong distortions from the EPI acquisition. Because of the nonrigid component a mask of the brain parenchyma helps greatly in obtaining a meaningful transform.
*The DTI estimation provides an automated mask for the DTI_baseline scan, but we have no mask for the T2. We can either obtain one through separate segmentation or by sending the DTI_mask through an additional registration step. In this example we show the latter.
*thus the full pipeline is this:
:#Affine align T2-T1, incl. resampled T2 volume = T2r
:#Affine+BSpline align of DTI_baseline to T2r (unmasked)
:#Resample DTI_mask with above BSpline -> mask for the T2r
:#repeat Affine+BSpline align of DTI_base to T2r, WITH masks
:#resample DTI with result Affine+BSpline transform
=== Procedures ===
*'''Phase I: Preprocessing: Build DWI mask + baseline'''
#open the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/DiffusionWeightedMasking ''Modules:Diffusion:DiffusionWeightedImages:DiffusionWeightedVolumeMasking'' ] module
##''Input DWI Volume'': "DWI"
##''Output Baseline Volume'': ''Create New Volume'', rename to "DWI_baseline"
##''Output Threshold Mask'': ''Create New Volume'', rename to "DWI_mask"
##Leave other settings at default; click ''Apply''
*'''Phase II: Preprocessing: Convert DWI -> DTI'''
#open [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/DiffusionTensorEstimation "Diffusion Tensor Estimation" module] (menu: Diffusion:DiffusionWeightedImages: DiffusionTensorEstimation)
##''Input DWI Volume'': DWI_iso,
##''Output DTI Volume'': create new, rename to "DTI_iso"
##''Output Baseline Volume'': create new, rename to "DWI_iso_baseline"
#Click: Apply
*'''Phase III: register T2 to T1'''
#open the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS) module]
##''Fixed Image Volume'': T1
##''Moving Image Volume'': T2
##Output Settings:
###''Slicer BSpline Transform": none
###''Slicer Linear Transform'': create new transform, rename to "Xf1_T2-T1"
###''Output Image Volume'': create new volume, rename to "T2_Xf1"
##''Registration Phases'': check boxes for ''Rigid'' and ''Affine''
##''Main Parameters'':
###''Number Of Samples'': 200,000
##Leave all other settings at default
##click: Apply; runtime < 10 sec (MacPro QuadCore 2.4GHz)
*'''Phase IV: Register DTI (masked)'''
#open the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS) module]
##''Fixed Image Volume'': FLAIR_Xf1
##''Moving Image Volume'': DWI_iso_baseline
##Output Settings:
###''Slicer BSpline Transform": create new transform, rename to "Xf2_DTI-T1"
###''Slicer Linear Transform'': none
###''Output Image Volume'': create new volume, rename to DWI_baseline_Xf2
##''Regstration Phases'': check boxes for ''Rigid'', ''Affine'' and ''BSpline''
##''Main Parameters'':
###''Number Of Samples'': 300,000
###''B-Spline Grid Size'': 7,7,5
##''Mask Option'': select ''ROIAUTO'' button
###''(ROIAUTO) Output fixed mask'': create new volume
###''(ROIAUTO) Output moving mask'': create new volume
##Leave all other settings at default
##click: Apply; runtime 1-2 min (MacPro QuadCore 2.4GHz)
*'''Phase V: Resample DTI'''
#Open the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/ResampleDTI ''Resample DTI Volume'' module] (under ''All Modules'' menu; note this is distinct from the ResampleScalarVectorDWIVolume used above)
##''Input Volume'': DTI
##''Output Volume'': create new DTI Volume, rename to ''DTI_Xf2''
##''Reference Volume'': T2_Xf1
##''Transform Node'': select "Xf2_DTI-T1'' created above
##check box: ''displacement''
#leave all other settings at defaults
#Click Apply; runtime ~ 3 min.
#set T1 or FLAIR as background and the new ''DTI_Xf2'' volume as foreground
#Move fade slider to see DTI overlay onto the structural image

=== Registration Results===
[[Image:RegLib_C29_registered.gif|500px|Registered DTI superimposed on SPGR and T2]] registered (cycles show T1 and T2 and color DTI overlay)<br>
<br>

Projects:RegistrationLibrary:RegLib C29

2013-05-09T19:54:42Z

Meier: /* Registration Results */

File:RegLib C29 registered2.gif

2013-05-09T19:54:19Z

Meier:

Projects:RegistrationDocumentation:RegLibTable

2012-08-13T15:37:33Z

Meier: /* Registration Library Cases : Sortable Table */

[[Projects:RegistrationDocumentation:UseCaseInventory|back to Library Main Page]] <br>

= Registration Library Cases : Sortable Table =
to link to the library case page, click on the thumbnail image, to link to the toolbox documentation, click on the link in the toolbox column. To sort the table by a category, click on the sort icon in the column header.<br>
Legend:
:*[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]<small> this case is up to date for version '''4.1'''</small> <br>
:*[[Image:Slicer_cvers_banner.png‎|60px|this case is up to date for version '''3.6.3''']]<small> this case is up to date for version '''3.6.3'''</small> <br>
:*[[Image:Slicer3-6Announcement-v1.png‎‎|60px| this case is up to date for version 3.6.1]]<small> this case is up to date for version 3.6.1</small><br>
:*[[Image:UnderConstruction_xparent.png‎|60px| these cases are not yet registered / under development]]<small> these cases are not yet registered / under development or presented as "challenge" cases for which no solution is avail. with the current Slicer tools. Some of these may have solutions with developer/extension modules or methods under development. Please contact the [mailto:slicer-users@bwh.harvard.edu Slicer-User List] for inquiries.</small><br>

{| class="wikitable sortable labelpage labelpagetable" border="1"
|-
! id
! thumbnail
! structure
! pathology
! DOF
! toolbox
! modality
! description
! status
|-
| 1
| [[Image:RegUC2_thumb_t0.png|60px|lleft|RegLib C01: Tumor change assessment|link=Projects:RegistrationLibrary:RegLib_C01]]
| brain
| meningioma
| 12
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| MRI T1
| change detection, tumor follow-up
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 2
|[[Image:RLib02_SPGR.png|60px|lleft|RegLib C02: MS multispectral alignment|link=Projects:RegistrationLibrary:RegLib_C02]]
| brain
| multiple sclerosis
| 12
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI T2 FLAIR
|
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 3
| [[Image:RegLib_C03_DTIVol_axial.png|60px|lleft|RegLib C03: DTI alignment|link=Projects:RegistrationLibrary:RegLib_C03]]
| brain
| tumor
| nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:DeformableB-SplineRegistration-Documentation-3.6 Fast Nonrigid BSpline]
| DTI
| align DTI volume with structural reference scan (T2)
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 4
| [[Image:Reglib_C04_Thumb_PD1.jpg‎|60px|lleft|RegLib C04: MS Lesion baseline|link=Projects:RegistrationLibrary:RegLib_C04]]
| Brain
| multiple sclerosis
| 12
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit] or [http://www.slicer.org/slicerWiki/index.php/Modules:RegisterImages-Documentation-3.6 Expert Automated]
| MRI PD/T2 T1Gd
| align 2 sets of multi-contrast MRI for lesion change assessment
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 5
| [[Image:RegLib C05 KneeMRI1.png|60px|lleft|RegLib 05: Knee MRI subject 1|link=Projects:RegistrationLibrary:RegLib_C05]]
| knee
| N/A
| 12
| [http://www.slicer.org/slicerWiki/index.php/Modules:PythonSurfaceICPRegistration-Documentation-3.6 Surface Registration]
| MRI
| inter-subject alignment of knee MRI for atlas-based segmentation
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 6
| [[Image:RegLib C06 BreastMRIPostRx.png|60px|lleft|RegLib 06: Breast MRI|link=Projects:RegistrationLibrary:RegLib_C06]]
| breast
| tumor
| 12 + nonrigid
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| MRI
| post-intervention assessment of breast cancer
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 7
| [[Image:RegLib C07_Thumb1.png|60px|lleft|RegLib 07: Prostate baseline|link=Projects:RegistrationLibrary:RegLib_C07]]
| prostate
| N/A
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| change-assessment in post-intervention MRI follow-up
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 8
| [[Image:RegLib_C08_WholeBodyPET-CT1.png|60px|lleft|RegLib C08: PET-CT1|link=Projects:RegistrationLibrary:RegLib_C08]]
| abdominal, thoracic
| path
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:AffineRegistration-Documentation-3.6 Fast Affine] + [http://www.slicer.org/slicerWiki/index.php/Modules:DeformableB-SplineRegistration-Documentation-3.6 Fast Nonrigid BSpline] or [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| PET-CT
| follow-up change assessment from combined whole-body PET-CT pair
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 9
| [[Image:RegLib_C09_Thumb2.png|70px|lleft|RegLib C09: T1 SPGR|link=Projects:RegistrationLibrary:RegLib_C09]]
| brain
| infarct
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| fMRI
| align fMRI with structural reference (T1)
| [[Image:Slicer_cvers_banner.png|70px|This case is complete and up to date for version 3.6.3]]
|-
| 10
| [[Image:RegLib_C10_EMAtlas2.png|60px|lleft|Probabilistic Tissue Atlas|link=Projects:RegistrationLibrary:RegLib_C10]]
| brain
| N/A
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:AffineRegistration-Documentation-3.6 Fast Affine] + [http://www.slicer.org/slicerWiki/index.php/Modules:DeformableB-SplineRegistration-Documentation-3.6 Fast Nonrigid BSpline]
| MRI
| align probabilistic tissue atlas with target brain for guiding EM tissue class segmentation
| [[Image:Slicer3-6Announcement-v1.png‎|70px|This case is complete and up to date for version 3.6.1]]
|-
| 11
| [[Image:RegLib_C11_AtlasMerge_1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C11]]
| brain
| none
| 12
| [http://www.slicer.org/slicerWiki/index.php/Modules:PythonSurfaceICPRegistration-Documentation-3.6 Surface Registration]
| MRI / labelmaps
| co-register surface models of thalamus for two separate subjects, merging anatomical labelmaps
| [[Image:Slicer3-6Announcement-v1.png‎|70px|This case is complete and up to date for version 3.6.1]]
|-
| 12
| [[Image:RegLib_C12_LiverTumor_MRI.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C12]]
| liver
| tumor
| nonrigid
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| MRI + CT
| Liver tumor ablation #1: intra-operative MRI to pre-op CT.
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
|-
| 13
| [[Image:RegLib_C13_LiverTumor2_CTpost.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C13]]
| liver
| tumor
| nonrigid
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| CT + MRI
| Liver tumor ablation : post-operative CT to pre-op CT & MRI
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 14
| [[Image:RegLib_C14_Thumb_PET.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C14]]
| brain
| N/A
| 12
| [http://www.slicer.org/slicerWiki/index.php/Modules:RegisterImages-Documentation-3.6 Expert Automated] or [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| PET + MRI
| alignment of brain PET to structural MRI, with adjustments to MRI aspect ratio and orientation.
| [[Image:Slicer3-6Announcement-v1.png‎|70px|This case is complete and up to date for version 3.6.1]]
|-
| 15
| [[Image:RegLib_C15_Thumb.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C15]]
| brain
| none
| 6
| [http://www.slicer.org/slicerWiki/index.php/Modules:ACPCTransform-Documentation-3.6 AC-PC Transform]
| MRI
| Realigning a single brain MRI along the anterior-posterior commissure line.
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 16
| [[Image:RegLib_C16_Brain0.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C16]]
| brain
| N/A
| 6
| [http://www.slicer.org/slicerWiki/index.php/Modules:Transforms-Documentation-3.6 Manual Registration:Transforms]
| MRI
| manually align FLAIR MRI with anatomical reference T1.
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 17
| [[Image:RegLib_C17_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C17]]
| kidney
| tumor
| affine
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| CT + MRI
| kidney tumor ablation : intra-operative CT to pre-op MRI
| [[Image:Slicer_cvers_banner.png‎|60px|this case is up to date for version '''3.6.3''']]
|-
| 18
| [[Image:RegLib_C18_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C18]]
| brain
| healthy, aging
| 12
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| align brain MRI both across and within exams
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 19
| [[Image:RegLib_C19_thumb_all.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C19]]
| brain
| healthy
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit] & [http://www.slicer.org/slicerWiki/index.php/Modules:DeformableB-SplineRegistration-Documentation-3.6 Fast nonrigid BSpline]
| MRI
| multi-stage inter- and intra-subject MRI registration
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 20
| [[Image:RegLib_C20_Thumb1.png|60px|lleft|RegLib C20: PET-CT|link=Projects:RegistrationLibrary:RegLib_C20]]
| abdominal, thoracic
| N/A
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| PET-CT
| follow-up change assessment from combined whole-body PET-CT pair
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 21
| [[Image:RegLib_C21_Thumb1.png|60px|lleft|RegLib C21: knee MRI|link=Projects:RegistrationLibrary:RegLib_C21]]
| knee
| N/A
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| inter-subject knee registration to build priors for cartilage segmentation
| [[Image:Slicer_cvers_banner.png‎|60px|this case is up to date for version '''3.6.3''']]
|-
| 27
| [[Image:RegLib27_DTI.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C27]]
| brain
| tumor
| 12 + nonrigid
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| DTI
| Alignment of DTI scan to structural reference T1-SPGR for surgical planning (tumor resection)
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 28
| [[Image:RegLib_C28_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C28]]
| vertebra
| spine cancer
| 12
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| CT
| Alignment of in vitro CT of spinal vertebra before and after damage
| [[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 29
| [[Image:RegLib_C29_Thumb.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C29]]
| brain
| tumor
| 12 + nonrigid
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| DTI
| Alignment of DTI scan to structural reference T2/T1-SPGR for surgical planning (tumor resection)
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 30
| [[Image:RegLib_C30_Thumb3.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C30]]
| brain
| N/A
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| DTI
| Alignment of DTI scan to structural reference T1 direct. No T2 available.
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 31
| [[Image:RegLib_C31_Thumb6.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C31]]
| brain
| TBI
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| intra- and inter-exam registration of multi-contrast MRI follow-up in TBI
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 32
| [[Image:RegLib_C30_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C30]]
| brain
| N/A
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| DTI
| Alignment of DTI scan: inverse direction: aligning structural reference to DTI.
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 33
| [[Image:RegLib_C33_Thumb4.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C33]]
| brain
| N/A
| 12 + nonrigid
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| DTI
| Alignment of hi-res multi contrast exam, incl. T1Gd FLAIR and DTI to T1 reference
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 34
| [[Image:RegLib_C34_Thumb2.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C34]]
| animal
| N/A
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| Alignment of mouse brain MRI atlas or different age
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 35
| [[Image:RegLibC35_Thumb2.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C35]]
| animal
| N/A
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:SurfaceRegistration Surface Registration]
| MRI
| Alignment of mouse colon MRI
| [[Image:UnderConstruction_xparent.png|40px|left|This is a challenge case / currently unsolved]]
|-
| 37
| [[Image:RegLib_C37_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C37]]
| brain
| tumor
| 6+12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| Alignment of intra-subject MRI for therapy assessment
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 38
| [[Image:RegLib_C38_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C38]]
| brain
| TBI
| 12 + nonrigid
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| MRI
| intra- and inter-exam registration of multi-contrast MRI follow-up in TBI at 3T
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 39
| [[Image:RegLib_C39_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C39]]
| vertebra
| spine cancer
| 12
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| CT
| Alignment of in vitro CT of thoracic vertebra before and after damage
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.3]]
|-
| 40
| [[Image:RegLib_C40_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C40]]
| wood sample
| materials science
| 12+nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| CT
| Alignment of in micro CT of wood samples to test hygromechanical behavior.
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.3]]
|-
| 41
| [[Image:RegLib_C41_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C41]]
| Mouse Brain
|
| 12+nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| Alignment of mouse brain MRI for group comparison
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.3]]
|-
| 42
| [[Image:RegLib_C42_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C42]]
| Infant Brain
| Autism
| 12+nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| Alignment of in longitudinal MRI of infant with autism (2-4 years)
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.3]]
|-
| 43
| [[Image:RegLib_C43_Thumb1b.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C43]]
| vertebrae/spine
| cancer
| rigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:PythonSurfaceICPRegistration-Documentation-3.6 Surface Registration]
| CT/3D models
| Analysis of structural integrity change
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.4]]
|-
| 44
| [[Image:RegLib_C44_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C44]]
| Pelvis
| N/A
| 12+nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| CT
| Analysis of inter-subject shape differences via nonrigid deformation/registration
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.3]]
|-
| 46
| [[Image:RegLib_C46_Thumb2.gif|60px|left|link=Projects:RegistrationLibrary:RegLib_C46]]
| dynamic lung MRI
|
| nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| Alignment of serial 2D lung MRI to assess dynamics
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.3]]
|-
| 47
| [[Image:RegLib_C12_LiverTumor_MRI.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C47]]
| liver
| tumor
| nonrigid
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| MRI + CT
| Liver tumor ablation: intra-op MRI to intra-op CT.
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
|}

Projects:RegistrationDocumentation:UseCaseInventory:Abdominal

2012-08-13T15:36:57Z

Meier: /* Case Inventory Abdominal */

Projects:RegistrationLibrary:RegLib C07

2012-08-13T15:35:44Z

Meier: /* Procedures */

Projects:RegistrationLibrary:RegLib C07

2012-08-13T15:35:07Z

Meier: /* Download */

Projects:RegistrationLibrary:RegLib C07

2012-08-13T15:34:42Z

Meier: /* Procedures */

Projects:RegistrationLibrary:RegLib C07

2012-08-13T15:33:38Z

Meier: /* Procedures */

Projects:RegistrationLibrary:RegLib C07

2012-08-13T15:32:51Z

Meier: /* Procedures */

Projects:RegistrationLibrary:RegLib C07

2012-08-13T15:21:55Z

Meier: /* Procedures */

Projects:RegistrationLibrary:RegLib C07

2012-08-13T15:21:12Z

Meier:

[[Projects:ARRASuplements|Back to ARRA main page]] <br>
[[Projects:RegistrationDocumentation|Back to Registration main page]] <br>
[[Projects:RegistrationDocumentation:UseCaseInventory|Back to Registration Use-case Inventory]] <br>

== <small>updated for '''v4.1'''</small> [[Image:Slicer4_RegLibLogo.png|150px]] Slicer Registration Library Case #07: Prostate MRI follow-up ==

=== Input ===
{| style="color:#bbbbbb; " cellpadding="10" cellspacing="0" border="0"
|[[Image:RegLib_C07_Thumb1.png|150px|lleft|this is the fixed reference image. All images are aligned into this space]]
|[[Image:RegArrow_NonRigid.png|100px|lleft]]
|[[Image:RegLib_C07_Thumb2.png|150px|lleft|this is the time series of 2D images to be registered with the reference]]
|-
|fixed:prostate MRI<br>day 1
|
|moving:prostate MRI<br>day 42
|}

=== Modules ===
*'''Slicer 3.6.1 recommended modules:
**[http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BrainsFit]'''
**[http://www.slicer.org/slicerWiki/index.php/Modules:N4ITKBiasFieldCorrection-Documentation-3.6 N4ITKBiasFieldCorrection module]
**[http://www.slicer.org/slicerWiki/index.php/Modules:CropVolume-Documentation-3.6 Crop Volume module]

===Objective / Background ===
Evaluate changes
=== Keywords ===
MRI, prostate, follow-up

===Input Data===
*reference/fixed : axial MRI 256x256x36 ,0.7 x 0.7 x 4mm voxel size
*moving: axial MRI 256x256x20 ,0.8 x 0.8 x 5mm voxel size

===Download ===
*Data
**[[Media:RegLib_C07_Data.zip‎ ‎|'''RegLib_C07_Data''' : original image series, result transforms and images, presets, Slicer Scene <small> (zip file 18 MB) </small>]]'''
**[[Media:RegLib_C07_Presets.mrml ‎|'''Parameter Presets'' <small> (.mrml text file 20 kB file 20 kB) </small>]]'''
[[Projects:RegistrationDocumentation:ParameterPresetsTutorial|Link to User Guide: How to Load/Save Registration Parameter Presets]]

=== Notes / Overall Strategy ===
*voxel size differs between the two images, also anisotropy is high: for the fine tuning a resampling to isotropic voxels for both volumes is recommended
*the large FOV includes a lot of additional image content that can be useful in constraining the alignment but also limits precision on the region of interest. Ev. cropping or masking to an ROI containing the prostate only is likely to improve the quality of the final registration
*the surface coils cause strong field inhomogeneity artifacts, apparent as strong intensity bias in both images. Bias correcion is recommended as preprocessing step.
*Overall strategy:
:#Bias correction of both images
:#Affine automated registration of Day42->Day1
:#Low-level BSpline registration (5x5x3) on global image, using above affine as starting point
;#Crop both images to prostate region only, resample to isotropic sizes
:#and apply above registration to cropped version of Day42
:#BSpline registration of cropped images only
:#Reapply final transform to entire (uncropped image)

=== Procedures ===
*'''Phase I: Bias field correction'''
#load reference image and one moving image from the series
#open [http://www.slicer.org/slicerWiki/index.php/Modules:N4ITKBiasFieldCorrection-Documentation-3.6 N4ITKBiasFieldCorrection module]
##optional: select presets ("N4_Day1_axial" ) for module parameters from ''Parameter Set'' menu, or:
##select "Day01_axial" as input image, create new "Day1_axial_N4" output image
##set ''Iterations'' to 90,60,40
##set ''BSpline grid resolution'' to 2,2,1
##set ''Shrink factor'' to 3
##click ''Apply''
#repeat above for the other image: "Day42_axial"
*'''Phase II: Affine Alignment'''
#go to [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit module]
##Set parameters via presets: ''Parameter set'' menu: "BRAINSFit_Xf1_Affine", '''or''' manually choose parameters below:
##Select ''Fixed Image'' = Day01_axial_n4 and ''Moving Image'' as "Day42_axial_n4"
##check boxes to include "rigid","scale", "skew" and "affine" registration phases
##increase''Number Of Samples'' to 300,000
##create new output transform from ''Slicer Linear Transform'' menu, rename to "Xf1_Affine" or similar
##click ''Apply''
##compare results with those shown below
*'''Phase II: BSpline Alignment Level 1'''
#go to [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit module]
##Set parameters via presets: ''Parameter set'' menu: "BRAINSFit_Xf2_BSpline", '''or''' manually choose parameters below:
##Select ''Fixed Image'' = Day01_axial_n4 and ''Moving Image'' as "Day42_axial_n4"
##check boxes to include "BSpline" registration phase only
##increase''Number Of Samples'' to 300,000
##create new output transform from ''Slicer BSpline Transform'' menu, rename to "Xf2_BSpline" or similar
##create new output volume from ''Output Image Volume'' menu, rename to "Day42_n4_Xf2_BSpline" or similar
##set BSpline Grid size: ''Number of Grid Subdivisions" to 5,5,3
##click ''Apply''
##compare results with those shown below
##Note that it is possible to do Phase I & II in a single step by also checking the "BSpline" phase box right away. However for pilot cases it is recommended to do them separately. If a combined registration fails it can be difficult to detect whether failure already occurred at the affine stage.
*'''Phase III: Cropping'''
#for a more refined alignment of the prostate only we first crop both images to the ROI only
#go to the [http://www.slicer.org/slicerWiki/index.php/Modules:CropVolume-Documentation-3.6 Crop Volume module]
##''Input Volume'', select "Day_01_axial_n4"
##''ROI'': select "New ROI"
##''Output Volume'': select "Create New Volume"
##You should see a blue box overlay in all 3 slice views. Click near the edges of the box to expand or contract it. In all 3 views place the box to enclose the prostate. Compare with results shown below.
##check the ''isotropic voxel size for output volume box''
##click on ''Do ROI resample''
##go to the ''Data'' module and rename the resampled output file to "Day_01_crop" or similar
#repeat above steps for "Day42_axial_n4"
#save your work
*'''Phase IV: BSpline Alignment Level 2'''
#you can now perform a second refined alignment on the cropped volumes only
#first resample the cropped volume with the initial BSpline above. Go to the [http://www.slicer.org/slicerWiki/index.php/Modules:ResampleScalarVectorDWIVolume-Documentation-3.6 ResampleScalarVectorDWIVolume module]
##Select your ""Day42_cropped" volume as input volume and the above "Xf2_BSpline" as input transform
##select "Day01_cropped" as reference
##create new volume "Day42_crop_Xf2" as output volume
##check ''output-to-input'' box, if not selected already
##click ''Apply''
##compare alignment of cropped volumes with results shown below
#go back to [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit module]
##you can now run a second BSpline with "Day01_cropped" as fixed and "Day42_cropped_Xf2" as moving volume
##set BSpline grid to 5,5,5
##leave other settings as for Phase II above.
##click ''Apply''
#compare alignment of cropped volumes with results shown below
#save your work

=== Registration Results===
{| style="color:#bbbbbb; " cellpadding="10" cellspacing="0" border="0"
|[[Image:RegLib_C07_unregistered.gif|300px|left|unregistered]]
|unregistered
|-
|[[Image:RegLib_C07_registered_Xf1.gif|300px|left|registered Xf1: Affine only]]
|registered Xf1: Affine only
|-
|[[Image:RegLib_C07_registered_Xf2.gif|300px|left|registered Xf2: Affine+BSpline]]
|registered Xf2: Affine+BSpline
|-
|[[Image:RegLib_C07_crop.png|300px|left|cropping of prostate ROI]]
|cropping of prostate ROI
|-
|[[Image:RegLib_C07_registered_Xf3.gif|300px|left|registered Xf3: Second Level BSpline on cropped and resampled images]]
|registered Xf3: Second Level BSpline on cropped and resampled images
|}

=== Acknowledgments ===
Images from the [http://prostatemrimagedatabase.com Prostate MR Image Database] (patient 1, exam 1).

Projects:RegistrationLibrary:RegLib C04:About

2012-08-13T15:05:44Z

Meier: /* Multiple Sclerosis Natural History Study */

== Multiple Sclerosis Natural History Study ==
The images in this case and the time-lapse movie shown below is from a unique longitudinal study, where MS patients underwent weekly to monthly examination including pre- and post-contrast MRI as well as a full clinical evaluation with assessment of clinical disability scores. Because the study was performed before effective disease-modifying treatments became available, it represents a unique snapshot of the natural history of MS that can no longer be reproduced today. The full power of this dataset on visualizing the unique dynamics of MS becomes apparent only after extensive preprocessing that involves spatial registration, intensity-normalization, partial volume filtering and other corrections. On average 25 separate exams were co-registered for each movie shown.
'''You will find more details in the following articles in the SPL publication database:'''
:1.[http://www.spl.harvard.edu/publications/item/view/1907 Seasonal Prevalence of MS Disease Activity. Neurology 2010]
:2.[http://www.spl.harvard.edu/publications/item/view/1172 MR Imaging Intensity Modeling of Damage and Repair In Multiple Sclerosis: Relationship of Short-Term Lesion Recovery to Progression and Disability. AJNR 2007]
:3.[http://www.spl.harvard.edu/publications/item/view/564 Time-series Modeling of Multiple Sclerosis Disease Activity: A Promising Window on Disease Progression and Repair Potential? Neurotherapeutics. 2007]
:4.[http://www.spl.harvard.edu/publications/item/view/87 MRI Time Series Modeling of MS Lesion Development. NeuroImage 2006]
:5.[http://www.spl.harvard.edu/publications/item/view/185 Time-series Analysis of MRI Intensity Patterns in Multiple Sclerosis. NeuroImage 2003]

For presentations including the animation below please cite [http://www.spl.harvard.edu/publications/item/view/185 Meier et al. , ''NeuroImage'' 2003; 20(2):1193-209.] for the image analysis methodology and [http://www.ncbi.nlm.nih.gov/pubmed/10713356 Weiner et al. , ''J Neuroimmunol'' 2000; 104(2):164-73.] for the data origin.
----
[[Image:MGrid_crop1_full.gif|Example time lapse of a single MS patient of the course of 1 year]]
<br>
[[Image:TSAGif_Recov.gif|Example time lapse animation of a single lesion showing significant recovery]]
[[Image:TSAGif_NoRecov.gif|Example time lapse animation of a single lesion showing little to no recovery]]
[[Image:TSAGif_Prop.gif|Example time lapse animation of a single lesion showing propagation along the WM]]

Projects:RegistrationLibrary:RegLib C04:About

2012-08-13T15:04:21Z

Meier:

== Multiple Sclerosis Natural History Study ==
The images in this case and the time-lapse movie shown below is from a unique longitudinal study, where MS patients underwent weekly to monthly examination including pre- and post-contrast MRI as well as a full clinical evaluation with assessment of clinical disability scores. Because the study was performed before effective disease-modifying treatments became available, it represents a unique snapshot of the natural history of MS that can no longer be reproduced today. The full power of this dataset on visualizing the unique dynamics of MS becomes apparent only after extensive preprocessing that involves spatial registration, intensity-normalization, partial volume filtering and other corrections.
'''You will find more details in the following articles in the SPL publication database:'''
:1.[http://www.spl.harvard.edu/publications/item/view/1907 Seasonal Prevalence of MS Disease Activity. Neurology 2010]
:2.[http://www.spl.harvard.edu/publications/item/view/1172 MR Imaging Intensity Modeling of Damage and Repair In Multiple Sclerosis: Relationship of Short-Term Lesion Recovery to Progression and Disability. AJNR 2007]
:3.[http://www.spl.harvard.edu/publications/item/view/564 Time-series Modeling of Multiple Sclerosis Disease Activity: A Promising Window on Disease Progression and Repair Potential? Neurotherapeutics. 2007]
:4.[http://www.spl.harvard.edu/publications/item/view/87 MRI Time Series Modeling of MS Lesion Development. NeuroImage 2006]
:5.[http://www.spl.harvard.edu/publications/item/view/185 Time-series Analysis of MRI Intensity Patterns in Multiple Sclerosis. NeuroImage 2003]

For presentations including the animation below please cite [http://www.spl.harvard.edu/publications/item/view/185 Meier et al. , ''NeuroImage'' 2003; 20(2):1193-209.] for the image analysis methodology and [http://www.ncbi.nlm.nih.gov/pubmed/10713356 Weiner et al. , ''J Neuroimmunol'' 2000; 104(2):164-73.] for the data origin.
----
[[Image:MGrid_crop1_full.gif|Example time lapse of a single MS patient of the course of 1 year]]
<br>
[[Image:TSAGif_Recov.gif|Example time lapse animation of a single lesion showing significant recovery]]
[[Image:TSAGif_NoRecov.gif|Example time lapse animation of a single lesion showing little to no recovery]]
[[Image:TSAGif_Prop.gif|Example time lapse animation of a single lesion showing propagation along the WM]]

File:TSAGif Prop.gif

2012-08-13T15:03:52Z

Meier: uploaded a new version of "File:TSAGif Prop.gif"

File:TSAGif Prop.gif

2012-08-13T15:01:14Z

Meier: uploaded a new version of "File:TSAGif Prop.gif"

Projects:RegistrationLibrary:RegLib C04:About

2012-08-13T14:59:28Z

Meier:

== Multiple Sclerosis Natural History Study ==
The images in this case and the time-lapse movie shown below is from a unique longitudinal study, where MS patients underwent weekly to monthly examination including pre- and post-contrast MRI as well as a full clinical evaluation with assessment of clinical disability scores. Because the study was performed before effective disease-modifying treatments became available, it represents a unique snapshot of the natural history of MS that can no longer be reproduced today. The full power of this dataset on visualizing the unique dynamics of MS becomes apparent only after extensive preprocessing that involves spatial registration, intensity-normalization, partial volume filtering and other corrections.
'''You will find more details in the following articles in the SPL publication database:'''
:1.[http://www.spl.harvard.edu/publications/item/view/1907 Seasonal Prevalence of MS Disease Activity. Neurology 2010]
:2.[http://www.spl.harvard.edu/publications/item/view/1172 MR Imaging Intensity Modeling of Damage and Repair In Multiple Sclerosis: Relationship of Short-Term Lesion Recovery to Progression and Disability. AJNR 2007]
:3.[http://www.spl.harvard.edu/publications/item/view/564 Time-series Modeling of Multiple Sclerosis Disease Activity: A Promising Window on Disease Progression and Repair Potential? Neurotherapeutics. 2007]
:4.[http://www.spl.harvard.edu/publications/item/view/87 MRI Time Series Modeling of MS Lesion Development. NeuroImage 2006]
:5.[http://www.spl.harvard.edu/publications/item/view/185 Time-series Analysis of MRI Intensity Patterns in Multiple Sclerosis. NeuroImage 2003]

For presentations including the animation below please cite [http://www.spl.harvard.edu/publications/item/view/185 Meier et al. , ''NeuroImage'' 2003; 20(2):1193-209.] for the image analysis methodology and [http://www.ncbi.nlm.nih.gov/pubmed/10713356 Weiner et al. , ''J Neuroimmunol'' 2000; 104(2):164-73.] for the data origin.
----
[[Image:MGrid_crop1_full.gif|Example time lapse of a single MS patient of the course of 1 year]]
[[Image:TSAGif_Recov.gif|Example time lapse animation of a single lesion showing significant recovery]]
[[Image:TSAGif_NoRecov.gif|Example time lapse animation of a single lesion showing little to no recovery]]
[[Image:TSAGif_Prop.gif|Example time lapse animation of a single lesion showing propagation along the WM]]

File:TSAGif Recov.gif

2012-08-13T14:56:43Z

Meier:

File:TSAGif Prop.gif

2012-08-13T14:52:34Z

Meier:

File:TSAGif NoRecov.gif

2012-08-13T14:52:11Z

Meier:

Projects:RegistrationLibrary:RegLib C04:About

2012-06-22T20:39:19Z

Meier: /* Multiple Sclerosis Natural History Study */

== Multiple Sclerosis Natural History Study ==
The images in this case and the time-lapse movie shown below is from a unique longitudinal study, where MS patients underwent weekly to monthly examination including pre- and post-contrast MRI as well as a full clinical evaluation with assessment of clinical disability scores. Because the study was performed before effective disease-modifying treatments became available, it represents a unique snapshot of the natural history of MS that can no longer be reproduced today. The full power of this dataset on visualizing the unique dynamics of MS becomes apparent only after extensive preprocessing that involves spatial registration, intensity-normalization, partial volume filtering and other corrections.
'''You will find more details in the following articles in the SPL publication database:'''
:1.[http://www.spl.harvard.edu/publications/item/view/1907 Seasonal Prevalence of MS Disease Activity. Neurology 2010]
:2.[http://www.spl.harvard.edu/publications/item/view/1172 MR Imaging Intensity Modeling of Damage and Repair In Multiple Sclerosis: Relationship of Short-Term Lesion Recovery to Progression and Disability. AJNR 2007]
:3.[http://www.spl.harvard.edu/publications/item/view/564 Time-series Modeling of Multiple Sclerosis Disease Activity: A Promising Window on Disease Progression and Repair Potential? Neurotherapeutics. 2007]
:4.[http://www.spl.harvard.edu/publications/item/view/87 MRI Time Series Modeling of MS Lesion Development. NeuroImage 2006]
:5.[http://www.spl.harvard.edu/publications/item/view/185 Time-series Analysis of MRI Intensity Patterns in Multiple Sclerosis. NeuroImage 2003]

For presentations including the animation below please cite [http://www.spl.harvard.edu/publications/item/view/185 Meier et al. , ''NeuroImage'' 2003; 20(2):1193-209.] for the image analysis methodology and [http://www.ncbi.nlm.nih.gov/pubmed/10713356 Weiner et al. , ''J Neuroimmunol'' 2000; 104(2):164-73.] for the data origin.
----
[[Image:MGrid_crop1_full.gif|Example time lapse of a single MS patient of the course of 1 year]]

Projects:RegistrationLibrary:RegLib C04:About

2012-06-22T20:36:57Z

Meier: /* Multiple Sclerosis Natural History Study */

== Multiple Sclerosis Natural History Study ==
The images in this case and the time-lapse movie shown below is from a unique longitudinal study, where MS patients underwent weekly to monthly examination including pre- and post-contrast MRI as well as a full clinical evaluation with assessment of clinical disability scores. Because the study was performed before effective disease-modifying treatments became available, it represents a unique snapshot of the natural history of MS that can no longer be reproduced today. The full power of this dataset on visualizing the unique dynamics of MS becomes apparent only after extensive preprocessing that involves spatial registration, intensity-normalization, partial volume filtering and other corrections.
'''You will find more details in the following articles in the SPL publication database:'''
:1.[http://www.spl.harvard.edu/publications/item/view/1907 Seasonal Prevalence of MS Disease Activity. Neurology 2010]
:2.[http://www.spl.harvard.edu/publications/item/view/1172 MR Imaging Intensity Modeling of Damage and Repair In Multiple Sclerosis: Relationship of Short-Term Lesion Recovery to Progression and Disability. AJNR 2007]
:3.[http://www.spl.harvard.edu/publications/item/view/564 Time-series Modeling of Multiple Sclerosis Disease Activity: A Promising Window on Disease Progression and Repair Potential? Neurotherapeutics. 2007]
:4.[http://www.spl.harvard.edu/publications/item/view/87 MRI Time Series Modeling of MS Lesion Development. NeuroImage 2006]
:5.[http://www.spl.harvard.edu/publications/item/view/185 Time-series Analysis of MRI Intensity Patterns in Multiple Sclerosis. NeuroImage 2003]

For presentations including the animation below please cite:
*[http://www.spl.harvard.edu/publications/item/view/185 Meier et al. , ''NeuroImage'' 2003; 20(2):1193-209.] for the image analysis methodology and [http://www.ncbi.nlm.nih.gov/pubmed/10713356 Weiner et al. , ''J Neuroimmunol'' 2000; 104(2):164-73.] for the data origin.
----
[[Image:MGrid_crop1_full.gif|Example time lapse of a single MS patient of the course of 1 year]]

Projects:RegistrationLibrary:RegLib C04:About

2012-06-22T20:35:26Z

Meier: /* Multiple Sclerosis Natural History Study */

== Multiple Sclerosis Natural History Study ==
The images in this case and the time-lapse movie shown below is from a unique longitudinal study, where MS patients underwent weekly to monthly examination including pre- and post-contrast MRI as well as a full clinical evaluation with assessment of clinical disability scores. Because the study was performed before effective disease-modifying treatments became available, it represents a unique snapshot of the natural history of MS that can no longer be reproduced today. The full power of this dataset on visualizing the unique dynamics of MS becomes apparent only after extensive preprocessing that involves spatial registration, intensity-normalization, partial volume filtering and other corrections.
'''You will find more details in the following articles in the SPL publication database:'''
:1.[http://www.spl.harvard.edu/publications/item/view/1907 Seasonal Prevalence of MS Disease Activity. Neurology 2010]
:2.[http://www.spl.harvard.edu/publications/item/view/1172 MR Imaging Intensity Modeling of Damage and Repair In Multiple Sclerosis: Relationship of Short-Term Lesion Recovery to Progression and Disability. AJNR 2007]
:3.[http://www.spl.harvard.edu/publications/item/view/564 Time-series Modeling of Multiple Sclerosis Disease Activity: A Promising Window on Disease Progression and Repair Potential? Neurotherapeutics. 2007]
:4.[http://www.spl.harvard.edu/publications/item/view/87 MRI Time Series Modeling of MS Lesion Development. NeuroImage 2006]
:5.[http://www.spl.harvard.edu/publications/item/view/185 Time-series Analysis of MRI Intensity Patterns in Multiple Sclerosis. NeuroImage 2003]

For presentations including the animation below please cite:
*[http://www.spl.harvard.edu/publications/item/view/185 Meier et al. , ''NeuroImage'' 2003; 20(2):1193-209.]
*[http://www.ncbi.nlm.nih.gov/pubmed/10713356 Weiner et al. , ''J Neuroimmunol'' 2000; 104(2):164-73.]
----
[[Image:MGrid_crop1_full.gif|Example time lapse of a single MS patient of the course of 1 year]]

Projects:RegistrationLibrary:RegLib C04:About

2012-06-22T20:34:45Z

Meier: /* Multiple Sclerosis Natural History Study */

== Multiple Sclerosis Natural History Study ==
The images in this case and the time-lapse movie shown below is from a unique longitudinal study, where MS patients underwent weekly to monthly examination including pre- and post-contrast MRI as well as a full clinical evaluation with assessment of clinical disability scores. Because the study was performed before effective disease-modifying treatments became available, it represents a unique snapshot of the natural history of MS that can no longer be reproduced today. The full power of this dataset on visualizing the unique dynamics of MS becomes apparent only after extensive preprocessing that involves spatial registration, intensity-normalization, partial volume filtering and other corrections.
'''You will find more details in the following articles in the SPL publication database:'''
:1.[http://www.spl.harvard.edu/publications/item/view/1907 Seasonal Prevalence of MS Disease Activity. Neurology 2010]
:2.[http://www.spl.harvard.edu/publications/item/view/1172 MR Imaging Intensity Modeling of Damage and Repair In Multiple Sclerosis: Relationship of Short-Term Lesion Recovery to Progression and Disability. AJNR 2007]
:3.[http://www.spl.harvard.edu/publications/item/view/564 Time-series Modeling of Multiple Sclerosis Disease Activity: A Promising Window on Disease Progression and Repair Potential? Neurotherapeutics. 2007]
:4.[http://www.spl.harvard.edu/publications/item/view/87 MRI Time Series Modeling of MS Lesion Development. NeuroImage 2006]
:5.[http://www.spl.harvard.edu/publications/item/view/185 Time-series Analysis of MRI Intensity Patterns in Multiple Sclerosis. NeuroImage 2003]

For presentations including the animation below please cite:
*[http://www.spl.harvard.edu/publications/item/view/185 Meier et al. , ''NeuroImage'' 2003 Oct;20(2):1193-209.]
*[http://www.ncbi.nlm.nih.gov/pubmed/10713356 Weiner et al. , ''J Neuroimmunol'' May 1;104(2):164-73.]
----
[[Image:MGrid_crop1_full.gif|Example time lapse of a single MS patient of the course of 1 year]]

2012 Summer Project Week:DifficultRegistration

2012-06-20T22:16:05Z

Meier: /* Key Investigators */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Ct-body-atlas.jpg
Image:Ct-body-cropped.jpg
Image:Ct-body-legs.jpg
Image:Mr-brain-atlas.jpg
Image:Mr-brain-tbi.jpg
Image:Mr-brain-rotated.jpg
Image:Mr-brain-rhesus.jpg
</gallery>

==Key Investigators==
* Erasmus Medical Center: Stefan Klein
* University College London: Marc Modat
* UNC: Aditya Gupta, Martin Styner
* BWH: Matthew Toews, Petter Risholm, Dominik Meier, William Wells

<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Objective</h3>
To identify solutions to difficult image registration problems that challenge the limits of current technology. Aspects of difficulty will include:
<ul>
<li>inter-subject registration
<li>truncation, missing tissue
<li>unknown initialization
<li>inter-species registration
<li>articulated deformation
</ul>
</div>

<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Approach, Plan</h3>
A set of difficult pair-wise registration problems will be considered. Participants will discuss workable solutions based on their expertise and background, and these solutions will be documented.
<br>
Registration cases can be found [http://www.matthewtoews.com/namic2012 here].
</div>

<div style="width: 40%; float: left;">

<h3>Progress</h3>TBA
*CT: atlas and torso have flipped orientation: Correction Xforms here: [[Media:FlipCT_Atlas+Torso.zip|Flip CT atlas&torso, zip file with 2 .tfm files]]
</div>
</div>

<div style="width: 97%; float: left;">

==Delivery Mechanism==
<b>Attention Participants:</b> Please log in and update/correct entries in the table below. For bonus points, please provide links or solutions to image registration problems on this page.<br>
<table border="1">
<th>Participant</th><th>Affiliation</th><th>Context</th><th>Techniques</th><th>Solutions/Links
</th><tr><td>
Steven Aylward</td><td>Kitware</td><td>CT, US, ressection, brain tumors, changing pathology, sliding organ</td><td>Sliding Geometry, Geometric Metamorphosis</td><td>
</td><tr><td>
Karl Diedrich</td><td>AZE</td><td>Rigid registration, abdomen</td><td>Multi-resolution registration</td><td>
</td><tr><td>
James Fishbaugh</td><td>SCI</td><td>Shape analysis and registration</td><td></td><td>
</td><tr><td>
Aditya Gupta</td><td>UNC</td><td>DTI, enlarged lateral ventricles</td><td></td><td>
</td><tr><td>
Stefan Klein</td><td>Erasmus Medical Center</td><td>General Registration</td><td></td><td>
</td><tr><td>
Ivan Kolesov</td><td>Georia Tech</td><td>Articulated, point-based registration</td><td></td><td>
</td><tr><td>
Dominik Meier</td><td>BWH</td><td>General registration</td><td>Slicer: BRAINS</td><td>
IntraOp:[[Image:IntraOp_Slicer-BRAINS_BSpline.gif|60px|lleft|IntraOp via BRAINS]]<br>
TBI:[[Image:TBI_Slicer-BRAINS_BSpline.gif|60px|lleft|TBI via BRAINS]]<br>
CT torso: FAILED</td><tr><td>
Marc Modat</td><td>UCL</td><td>Intra-op, longitudinal</td><td>NiftiReg</td><td>
</td><tr><td>
Albert Motillo</td><td>GE</td><td>Parsing CT, Detection</td><td></td><td>
</td><tr><td>
Simrin Nagpal</td><td>Queens University</td><td>CT/US registration</td><td></td><td>
</td><tr><td>
Samon Nuranian</td><td>UBC</td><td>US-guided intervension, spine</td><td></td><td>
</td><tr><td>
Andre Remi</td><td>UCLA</td><td>Longitudinal changes in TBI, tissue types</td><td></td><td>
</td><tr><td>
Peter Risholm</td><td>BWH</td><td>Brain, head and neck, radiation therapy</td><td>Probabilistic Uncertainty</td><td>
</td><tr><td>
Samira Sojoudi</td><td>UBC</td><td>Spine, CT/US registration</td><td></td><td>
</td><tr><td>
Matthew Toews</td><td>BWH</td><td>General registration</td><td>SIFT landmark correspondence</td><td>
</td><tr><td>
Bo Wang</td><td>Utah</td><td>TBI image segmentation</td><td></td><td>
</td><tr><td>
Kevin Wang</td><td>Princess Margaret Hospital</td><td>Adaptive radiation therapy, longitudinal</td><td></td><td>
</td><tr><td>
William Wells</td><td>BWH</td><td>Interventional applications</td><td>Theory: Segmentation, Registration</td><td></td>
<table>

== Links for Data ==
* [http://www.matthewtoews.com/namic2012 Matt's initial examples]
* [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:RegLibTable Slicer Registration Case Library]
* [http://dmip1.rad.jhmi.edu/xcat/ XCAT]
* [http://wiki.na-mic.org/Wiki/index.php/File:EnlargedLVCase_Normal.zip DTI Files Enlarged LV registration with normal control]
* [http://wiki.na-mic.org/Wiki/index.php/File:Krabbe_Controls_DWI.zip DWI Files Enlarged LV registration with normal control]
* [http://www.na-mic.org/Wiki/index.php/DBP3:UCLA#Data TBI Cases]
* [http://www.nitrc.org/projects/tumorsim/ TumorSim] longitudinal data: To appear at http://midas3.kitware.com

== Links for Tools & Methods ==
* Sliding Geometries Registration: http://public.kitware.com/Wiki/TubeTK
* Geometric Metamorphosis: https://github.com/calaTK/calaTK

== Links for Papers ==
* Sliding Geometries
** ISBI 2011: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3141338/
** Abdominal Imaging, MICCAI, 2011: http://www.springerlink.com/content/552824638l375645/
* Geometric MetaMorphosis
** MICCAI 2011: http://www.springerlink.com/content/7r077665012078r5/

</div>

File:FlipCT Atlas+Torso.zip

2012-06-20T22:15:24Z

Meier:

2012 Summer Project Week:DifficultRegistration

2012-06-20T22:14:10Z

Meier: /* Key Investigators */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Ct-body-atlas.jpg
Image:Ct-body-cropped.jpg
Image:Ct-body-legs.jpg
Image:Mr-brain-atlas.jpg
Image:Mr-brain-tbi.jpg
Image:Mr-brain-rotated.jpg
Image:Mr-brain-rhesus.jpg
</gallery>

==Key Investigators==
* Erasmus Medical Center: Stefan Klein
* University College London: Marc Modat
* UNC: Aditya Gupta, Martin Styner
* BWH: Matthew Toews, Petter Risholm, Dominik Meier, William Wells

<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Objective</h3>
To identify solutions to difficult image registration problems that challenge the limits of current technology. Aspects of difficulty will include:
<ul>
<li>inter-subject registration
<li>truncation, missing tissue
<li>unknown initialization
<li>inter-species registration
<li>articulated deformation
</ul>
</div>

<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Approach, Plan</h3>
A set of difficult pair-wise registration problems will be considered. Participants will discuss workable solutions based on their expertise and background, and these solutions will be documented.
<br>
Registration cases can be found [http://www.matthewtoews.com/namic2012 here].
</div>

<div style="width: 40%; float: left;">

<h3>Progress</h3>TBA
*CT: atlas and torso have flipped orientation: Correction Xforms here: [[Media:Xf0a_FlipAtlas.tfm|Flip CT atlas]] , [[Media:Xf0b_FlipTorso.tfm|Flip CT torso]]
</div>
</div>

<div style="width: 97%; float: left;">

==Delivery Mechanism==
<b>Attention Participants:</b> Please log in and update/correct entries in the table below. For bonus points, please provide links or solutions to image registration problems on this page.<br>
<table border="1">
<th>Participant</th><th>Affiliation</th><th>Context</th><th>Techniques</th><th>Solutions/Links
</th><tr><td>
Steven Aylward</td><td>Kitware</td><td>CT, US, ressection, brain tumors, changing pathology, sliding organ</td><td>Sliding Geometry, Geometric Metamorphosis</td><td>
</td><tr><td>
Karl Diedrich</td><td>AZE</td><td>Rigid registration, abdomen</td><td>Multi-resolution registration</td><td>
</td><tr><td>
James Fishbaugh</td><td>SCI</td><td>Shape analysis and registration</td><td></td><td>
</td><tr><td>
Aditya Gupta</td><td>UNC</td><td>DTI, enlarged lateral ventricles</td><td></td><td>
</td><tr><td>
Stefan Klein</td><td>Erasmus Medical Center</td><td>General Registration</td><td></td><td>
</td><tr><td>
Ivan Kolesov</td><td>Georia Tech</td><td>Articulated, point-based registration</td><td></td><td>
</td><tr><td>
Dominik Meier</td><td>BWH</td><td>General registration</td><td>Slicer: BRAINS</td><td>
IntraOp:[[Image:IntraOp_Slicer-BRAINS_BSpline.gif|60px|lleft|IntraOp via BRAINS]]<br>
TBI:[[Image:TBI_Slicer-BRAINS_BSpline.gif|60px|lleft|TBI via BRAINS]]<br>
CT torso: FAILED</td><tr><td>
Marc Modat</td><td>UCL</td><td>Intra-op, longitudinal</td><td>NiftiReg</td><td>
</td><tr><td>
Albert Motillo</td><td>GE</td><td>Parsing CT, Detection</td><td></td><td>
</td><tr><td>
Simrin Nagpal</td><td>Queens University</td><td>CT/US registration</td><td></td><td>
</td><tr><td>
Samon Nuranian</td><td>UBC</td><td>US-guided intervension, spine</td><td></td><td>
</td><tr><td>
Andre Remi</td><td>UCLA</td><td>Longitudinal changes in TBI, tissue types</td><td></td><td>
</td><tr><td>
Peter Risholm</td><td>BWH</td><td>Brain, head and neck, radiation therapy</td><td>Probabilistic Uncertainty</td><td>
</td><tr><td>
Samira Sojoudi</td><td>UBC</td><td>Spine, CT/US registration</td><td></td><td>
</td><tr><td>
Matthew Toews</td><td>BWH</td><td>General registration</td><td>SIFT landmark correspondence</td><td>
</td><tr><td>
Bo Wang</td><td>Utah</td><td>TBI image segmentation</td><td></td><td>
</td><tr><td>
Kevin Wang</td><td>Princess Margaret Hospital</td><td>Adaptive radiation therapy, longitudinal</td><td></td><td>
</td><tr><td>
William Wells</td><td>BWH</td><td>Interventional applications</td><td>Theory: Segmentation, Registration</td><td></td>
<table>

== Links for Data ==
* [http://www.matthewtoews.com/namic2012 Matt's initial examples]
* [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:RegLibTable Slicer Registration Case Library]
* [http://dmip1.rad.jhmi.edu/xcat/ XCAT]
* [http://wiki.na-mic.org/Wiki/index.php/File:EnlargedLVCase_Normal.zip DTI Files Enlarged LV registration with normal control]
* [http://wiki.na-mic.org/Wiki/index.php/File:Krabbe_Controls_DWI.zip DWI Files Enlarged LV registration with normal control]
* [http://www.na-mic.org/Wiki/index.php/DBP3:UCLA#Data TBI Cases]
* [http://www.nitrc.org/projects/tumorsim/ TumorSim] longitudinal data: To appear at http://midas3.kitware.com

== Links for Tools & Methods ==
* Sliding Geometries Registration: http://public.kitware.com/Wiki/TubeTK
* Geometric Metamorphosis: https://github.com/calaTK/calaTK

== Links for Papers ==
* Sliding Geometries
** ISBI 2011: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3141338/
** Abdominal Imaging, MICCAI, 2011: http://www.springerlink.com/content/552824638l375645/
* Geometric MetaMorphosis
** MICCAI 2011: http://www.springerlink.com/content/7r077665012078r5/

</div>

2012 Summer Project Week:DifficultRegistration

2012-06-20T22:10:29Z

Meier: /* Delivery Mechanism */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Ct-body-atlas.jpg
Image:Ct-body-cropped.jpg
Image:Ct-body-legs.jpg
Image:Mr-brain-atlas.jpg
Image:Mr-brain-tbi.jpg
Image:Mr-brain-rotated.jpg
Image:Mr-brain-rhesus.jpg
</gallery>

==Key Investigators==
* Erasmus Medical Center: Stefan Klein
* University College London: Marc Modat
* UNC: Aditya Gupta, Martin Styner
* BWH: Matthew Toews, Petter Risholm, Dominik Meier, William Wells

<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Objective</h3>
To identify solutions to difficult image registration problems that challenge the limits of current technology. Aspects of difficulty will include:
<ul>
<li>inter-subject registration
<li>truncation, missing tissue
<li>unknown initialization
<li>inter-species registration
<li>articulated deformation
</ul>
</div>

<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Approach, Plan</h3>
A set of difficult pair-wise registration problems will be considered. Participants will discuss workable solutions based on their expertise and background, and these solutions will be documented.
<br>
Registration cases can be found [http://www.matthewtoews.com/namic2012 here].
</div>

<div style="width: 40%; float: left;">

<h3>Progress</h3>TBA

</div>
</div>

<div style="width: 97%; float: left;">

==Delivery Mechanism==
<b>Attention Participants:</b> Please log in and update/correct entries in the table below. For bonus points, please provide links or solutions to image registration problems on this page.<br>
<table border="1">
<th>Participant</th><th>Affiliation</th><th>Context</th><th>Techniques</th><th>Solutions/Links
</th><tr><td>
Steven Aylward</td><td>Kitware</td><td>CT, US, ressection, brain tumors, changing pathology, sliding organ</td><td>Sliding Geometry, Geometric Metamorphosis</td><td>
</td><tr><td>
Karl Diedrich</td><td>AZE</td><td>Rigid registration, abdomen</td><td>Multi-resolution registration</td><td>
</td><tr><td>
James Fishbaugh</td><td>SCI</td><td>Shape analysis and registration</td><td></td><td>
</td><tr><td>
Aditya Gupta</td><td>UNC</td><td>DTI, enlarged lateral ventricles</td><td></td><td>
</td><tr><td>
Stefan Klein</td><td>Erasmus Medical Center</td><td>General Registration</td><td></td><td>
</td><tr><td>
Ivan Kolesov</td><td>Georia Tech</td><td>Articulated, point-based registration</td><td></td><td>
</td><tr><td>
Dominik Meier</td><td>BWH</td><td>General registration</td><td>Slicer: BRAINS</td><td>
IntraOp:[[Image:IntraOp_Slicer-BRAINS_BSpline.gif|60px|lleft|IntraOp via BRAINS]]<br>
TBI:[[Image:TBI_Slicer-BRAINS_BSpline.gif|60px|lleft|TBI via BRAINS]]<br>
CT torso: FAILED</td><tr><td>
Marc Modat</td><td>UCL</td><td>Intra-op, longitudinal</td><td>NiftiReg</td><td>
</td><tr><td>
Albert Motillo</td><td>GE</td><td>Parsing CT, Detection</td><td></td><td>
</td><tr><td>
Simrin Nagpal</td><td>Queens University</td><td>CT/US registration</td><td></td><td>
</td><tr><td>
Samon Nuranian</td><td>UBC</td><td>US-guided intervension, spine</td><td></td><td>
</td><tr><td>
Andre Remi</td><td>UCLA</td><td>Longitudinal changes in TBI, tissue types</td><td></td><td>
</td><tr><td>
Peter Risholm</td><td>BWH</td><td>Brain, head and neck, radiation therapy</td><td>Probabilistic Uncertainty</td><td>
</td><tr><td>
Samira Sojoudi</td><td>UBC</td><td>Spine, CT/US registration</td><td></td><td>
</td><tr><td>
Matthew Toews</td><td>BWH</td><td>General registration</td><td>SIFT landmark correspondence</td><td>
</td><tr><td>
Bo Wang</td><td>Utah</td><td>TBI image segmentation</td><td></td><td>
</td><tr><td>
Kevin Wang</td><td>Princess Margaret Hospital</td><td>Adaptive radiation therapy, longitudinal</td><td></td><td>
</td><tr><td>
William Wells</td><td>BWH</td><td>Interventional applications</td><td>Theory: Segmentation, Registration</td><td></td>
<table>

== Links for Data ==
* [http://www.matthewtoews.com/namic2012 Matt's initial examples]
* [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:RegLibTable Slicer Registration Case Library]
* [http://dmip1.rad.jhmi.edu/xcat/ XCAT]
* [http://wiki.na-mic.org/Wiki/index.php/File:EnlargedLVCase_Normal.zip DTI Files Enlarged LV registration with normal control]
* [http://wiki.na-mic.org/Wiki/index.php/File:Krabbe_Controls_DWI.zip DWI Files Enlarged LV registration with normal control]
* [http://www.na-mic.org/Wiki/index.php/DBP3:UCLA#Data TBI Cases]
* [http://www.nitrc.org/projects/tumorsim/ TumorSim] longitudinal data: To appear at http://midas3.kitware.com

== Links for Tools & Methods ==
* Sliding Geometries Registration: http://public.kitware.com/Wiki/TubeTK
* Geometric Metamorphosis: https://github.com/calaTK/calaTK

== Links for Papers ==
* Sliding Geometries
** ISBI 2011: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3141338/
** Abdominal Imaging, MICCAI, 2011: http://www.springerlink.com/content/552824638l375645/
* Geometric MetaMorphosis
** MICCAI 2011: http://www.springerlink.com/content/7r077665012078r5/

</div>

2012 Summer Project Week:DifficultRegistration

2012-06-20T22:10:08Z

Meier: /* Delivery Mechanism */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Ct-body-atlas.jpg
Image:Ct-body-cropped.jpg
Image:Ct-body-legs.jpg
Image:Mr-brain-atlas.jpg
Image:Mr-brain-tbi.jpg
Image:Mr-brain-rotated.jpg
Image:Mr-brain-rhesus.jpg
</gallery>

==Key Investigators==
* Erasmus Medical Center: Stefan Klein
* University College London: Marc Modat
* UNC: Aditya Gupta, Martin Styner
* BWH: Matthew Toews, Petter Risholm, Dominik Meier, William Wells

<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Objective</h3>
To identify solutions to difficult image registration problems that challenge the limits of current technology. Aspects of difficulty will include:
<ul>
<li>inter-subject registration
<li>truncation, missing tissue
<li>unknown initialization
<li>inter-species registration
<li>articulated deformation
</ul>
</div>

<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Approach, Plan</h3>
A set of difficult pair-wise registration problems will be considered. Participants will discuss workable solutions based on their expertise and background, and these solutions will be documented.
<br>
Registration cases can be found [http://www.matthewtoews.com/namic2012 here].
</div>

<div style="width: 40%; float: left;">

<h3>Progress</h3>TBA

</div>
</div>

<div style="width: 97%; float: left;">

==Delivery Mechanism==
<b>Attention Participants:</b> Please log in and update/correct entries in the table below. For bonus points, please provide links or solutions to image registration problems on this page.<br>
<table border="1">
<th>Participant</th><th>Affiliation</th><th>Context</th><th>Techniques</th><th>Solutions/Links
</th><tr><td>
Steven Aylward</td><td>Kitware</td><td>CT, US, ressection, brain tumors, changing pathology, sliding organ</td><td>Sliding Geometry, Geometric Metamorphosis</td><td>
</td><tr><td>
Karl Diedrich</td><td>AZE</td><td>Rigid registration, abdomen</td><td>Multi-resolution registration</td><td>
</td><tr><td>
James Fishbaugh</td><td>SCI</td><td>Shape analysis and registration</td><td></td><td>
</td><tr><td>
Aditya Gupta</td><td>UNC</td><td>DTI, enlarged lateral ventricles</td><td></td><td>
</td><tr><td>
Stefan Klein</td><td>Erasmus Medical Center</td><td>General Registration</td><td></td><td>
</td><tr><td>
Ivan Kolesov</td><td>Georia Tech</td><td>Articulated, point-based registration</td><td></td><td>
</td><tr><td>
Dominik Meier</td><td>BWH</td><td>General registration</td><td>Slicer: BRAINS</td><td>
IntraOp:[[Image:IntraOp_Slicer-BRAINS_BSpline.gif|60px|lleft|IntraOp via BRAINS]]
TBI:[[Image:TBI_Slicer-BRAINS_BSpline.gif|60px|lleft|TBI via BRAINS]]<br>
CT torso: FAILED</td><tr><td>
Marc Modat</td><td>UCL</td><td>Intra-op, longitudinal</td><td>NiftiReg</td><td>
</td><tr><td>
Albert Motillo</td><td>GE</td><td>Parsing CT, Detection</td><td></td><td>
</td><tr><td>
Simrin Nagpal</td><td>Queens University</td><td>CT/US registration</td><td></td><td>
</td><tr><td>
Samon Nuranian</td><td>UBC</td><td>US-guided intervension, spine</td><td></td><td>
</td><tr><td>
Andre Remi</td><td>UCLA</td><td>Longitudinal changes in TBI, tissue types</td><td></td><td>
</td><tr><td>
Peter Risholm</td><td>BWH</td><td>Brain, head and neck, radiation therapy</td><td>Probabilistic Uncertainty</td><td>
</td><tr><td>
Samira Sojoudi</td><td>UBC</td><td>Spine, CT/US registration</td><td></td><td>
</td><tr><td>
Matthew Toews</td><td>BWH</td><td>General registration</td><td>SIFT landmark correspondence</td><td>
</td><tr><td>
Bo Wang</td><td>Utah</td><td>TBI image segmentation</td><td></td><td>
</td><tr><td>
Kevin Wang</td><td>Princess Margaret Hospital</td><td>Adaptive radiation therapy, longitudinal</td><td></td><td>
</td><tr><td>
William Wells</td><td>BWH</td><td>Interventional applications</td><td>Theory: Segmentation, Registration</td><td></td>
<table>

== Links for Data ==
* [http://www.matthewtoews.com/namic2012 Matt's initial examples]
* [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:RegLibTable Slicer Registration Case Library]
* [http://dmip1.rad.jhmi.edu/xcat/ XCAT]
* [http://wiki.na-mic.org/Wiki/index.php/File:EnlargedLVCase_Normal.zip DTI Files Enlarged LV registration with normal control]
* [http://wiki.na-mic.org/Wiki/index.php/File:Krabbe_Controls_DWI.zip DWI Files Enlarged LV registration with normal control]
* [http://www.na-mic.org/Wiki/index.php/DBP3:UCLA#Data TBI Cases]
* [http://www.nitrc.org/projects/tumorsim/ TumorSim] longitudinal data: To appear at http://midas3.kitware.com

== Links for Tools & Methods ==
* Sliding Geometries Registration: http://public.kitware.com/Wiki/TubeTK
* Geometric Metamorphosis: https://github.com/calaTK/calaTK

== Links for Papers ==
* Sliding Geometries
** ISBI 2011: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3141338/
** Abdominal Imaging, MICCAI, 2011: http://www.springerlink.com/content/552824638l375645/
* Geometric MetaMorphosis
** MICCAI 2011: http://www.springerlink.com/content/7r077665012078r5/

</div>

2012 Summer Project Week:DifficultRegistration

2012-06-20T21:23:22Z

Meier: /* Delivery Mechanism */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Ct-body-atlas.jpg
Image:Ct-body-cropped.jpg
Image:Ct-body-legs.jpg
Image:Mr-brain-atlas.jpg
Image:Mr-brain-tbi.jpg
Image:Mr-brain-rotated.jpg
Image:Mr-brain-rhesus.jpg
</gallery>

==Key Investigators==
* Erasmus Medical Center: Stefan Klein
* University College London: Marc Modat
* UNC: Aditya Gupta, Martin Styner
* BWH: Matthew Toews, Petter Risholm, Dominik Meier, William Wells

<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Objective</h3>
To identify solutions to difficult image registration problems that challenge the limits of current technology. Aspects of difficulty will include:
<ul>
<li>inter-subject registration
<li>truncation, missing tissue
<li>unknown initialization
<li>inter-species registration
<li>articulated deformation
</ul>
</div>

<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Approach, Plan</h3>
A set of difficult pair-wise registration problems will be considered. Participants will discuss workable solutions based on their expertise and background, and these solutions will be documented.
<br>
Registration cases can be found [http://www.matthewtoews.com/namic2012 here].
</div>

<div style="width: 40%; float: left;">

<h3>Progress</h3>TBA

</div>
</div>

<div style="width: 97%; float: left;">

==Delivery Mechanism==
<b>Attention Participants:</b> Please log in and update/correct entries in the table below. For bonus points, please provide links or solutions to image registration problems on this page.<br>
<table border="1">
<th>Participant</th><th>Affiliation</th><th>Context</th><th>Techniques</th><th>Solutions/Links
</th><tr><td>
Steven Aylward</td><td>Kitware</td><td>CT, US, ressection, brain tumors, changing pathology, sliding organ</td><td>Sliding Geometry, Geometric Metamorphosis</td><td>
</td><tr><td>
Karl Diedrich</td><td>AZE</td><td>Rigid registration, abdomen</td><td>Multi-resolution registration</td><td>
</td><tr><td>
James Fishbaugh</td><td>SCI</td><td>Shape analysis and registration</td><td></td><td>
</td><tr><td>
Aditya Gupta</td><td>UNC</td><td>DTI, enlarged lateral ventricles</td><td></td><td>
</td><tr><td>
Stefan Klein</td><td>Erasmus Medical Center</td><td>General Registration</td><td></td><td>
</td><tr><td>
Ivan Kolesov</td><td>Georia Tech</td><td>Articulated, point-based registration</td><td></td><td>
</td><tr><td>
Dominik Meier</td><td>BWH</td><td>General registration</td><td>Slicer: BRAINS</td><td>
IntraOp:[[Image:IntraOp_Slicer-BRAINS_BSpline.gif|60px|lleft|IntraOp via BRAINS]]
TBI:[[Image:TBI_Slicer-BRAINS_BSpline.gif|60px|lleft|TBI via BRAINS]]</td><tr><td>
Marc Modat</td><td>UCL</td><td>Intra-op, longitudinal</td><td>NiftiReg</td><td>
</td><tr><td>
Albert Motillo</td><td>GE</td><td>Parsing CT, Detection</td><td></td><td>
</td><tr><td>
Simrin Nagpal</td><td>Queens University</td><td>CT/US registration</td><td></td><td>
</td><tr><td>
Samon Nuranian</td><td>UBC</td><td>US-guided intervension, spine</td><td></td><td>
</td><tr><td>
Andre Remi</td><td>UCLA</td><td>Longitudinal changes in TBI, tissue types</td><td></td><td>
</td><tr><td>
Peter Risholm</td><td>BWH</td><td>Brain, head and neck, radiation therapy</td><td>Probabilistic Uncertainty</td><td>
</td><tr><td>
Samira Sojoudi</td><td>UBC</td><td>Spine, CT/US registration</td><td></td><td>
</td><tr><td>
Matthew Toews</td><td>BWH</td><td>General registration</td><td>SIFT landmark correspondence</td><td>
</td><tr><td>
Bo Wang</td><td>Utah</td><td>TBI image segmentation</td><td></td><td>
</td><tr><td>
Kevin Wang</td><td>Princess Margaret Hospital</td><td>Adaptive radiation therapy, longitudinal</td><td></td><td>
</td><tr><td>
William Wells</td><td>BWH</td><td>Interventional applications</td><td>Theory: Segmentation, Registration</td><td></td>
<table>

== Links for Data ==
* [http://www.matthewtoews.com/namic2012 Matt's initial examples]
* [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:RegLibTable Slicer Registration Case Library]
* [http://dmip1.rad.jhmi.edu/xcat/ XCAT]
* [http://wiki.na-mic.org/Wiki/index.php/File:EnlargedLVCase_Normal.zip DTI Files Enlarged LV registration with normal control]
* [http://wiki.na-mic.org/Wiki/index.php/File:Krabbe_Controls_DWI.zip DWI Files Enlarged LV registration with normal control]
* [http://www.na-mic.org/Wiki/index.php/DBP3:UCLA#Data TBI Cases]
* [http://www.nitrc.org/projects/tumorsim/ TumorSim] longitudinal data: To appear at http://midas3.kitware.com

== Links for Tools & Methods ==
* Sliding Geometries Registration: http://public.kitware.com/Wiki/TubeTK
* Geometric Metamorphosis: https://github.com/calaTK/calaTK

== Links for Papers ==
* Sliding Geometries
** ISBI 2011: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3141338/
** Abdominal Imaging, MICCAI, 2011: http://www.springerlink.com/content/552824638l375645/
* Geometric MetaMorphosis
** MICCAI 2011: http://www.springerlink.com/content/7r077665012078r5/

</div>

2012 Summer Project Week:DifficultRegistration

2012-06-20T21:22:35Z

Meier: /* Delivery Mechanism */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Ct-body-atlas.jpg
Image:Ct-body-cropped.jpg
Image:Ct-body-legs.jpg
Image:Mr-brain-atlas.jpg
Image:Mr-brain-tbi.jpg
Image:Mr-brain-rotated.jpg
Image:Mr-brain-rhesus.jpg
</gallery>

==Key Investigators==
* Erasmus Medical Center: Stefan Klein
* University College London: Marc Modat
* UNC: Aditya Gupta, Martin Styner
* BWH: Matthew Toews, Petter Risholm, Dominik Meier, William Wells

<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Objective</h3>
To identify solutions to difficult image registration problems that challenge the limits of current technology. Aspects of difficulty will include:
<ul>
<li>inter-subject registration
<li>truncation, missing tissue
<li>unknown initialization
<li>inter-species registration
<li>articulated deformation
</ul>
</div>

<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Approach, Plan</h3>
A set of difficult pair-wise registration problems will be considered. Participants will discuss workable solutions based on their expertise and background, and these solutions will be documented.
<br>
Registration cases can be found [http://www.matthewtoews.com/namic2012 here].
</div>

<div style="width: 40%; float: left;">

<h3>Progress</h3>TBA

</div>
</div>

<div style="width: 97%; float: left;">

==Delivery Mechanism==
<b>Attention Participants:</b> Please log in and update/correct entries in the table below. For bonus points, please provide links or solutions to image registration problems on this page.<br>
<table border="1">
<th>Participant</th><th>Affiliation</th><th>Context</th><th>Techniques</th><th>Solutions/Links
</th><tr><td>
Steven Aylward</td><td>Kitware</td><td>CT, US, ressection, brain tumors, changing pathology, sliding organ</td><td>Sliding Geometry, Geometric Metamorphosis</td><td>
</td><tr><td>
Karl Diedrich</td><td>AZE</td><td>Rigid registration, abdomen</td><td>Multi-resolution registration</td><td>
</td><tr><td>
James Fishbaugh</td><td>SCI</td><td>Shape analysis and registration</td><td></td><td>
</td><tr><td>
Aditya Gupta</td><td>UNC</td><td>DTI, enlarged lateral ventricles</td><td></td><td>
</td><tr><td>
Stefan Klein</td><td>Erasmus Medical Center</td><td>General Registration</td><td></td><td>
</td><tr><td>
Ivan Kolesov</td><td>Georia Tech</td><td>Articulated, point-based registration</td><td></td><td>
</td><tr><td>
Dominik Meier</td><td>BWH</td><td>General registration</td><td>Slicer: BRAINS</td><td>
[[Image:IntraOp_Slicer-BRAINS_BSpline.gif|60px|lleft|IntraOp via BRAINS]]
[[Image:TBI_Slicer-BRAINS_BSpline.gif|60px|lleft|TBI via BRAINS]]</td><tr><td>
Marc Modat</td><td>UCL</td><td>Intra-op, longitudinal</td><td>NiftiReg</td><td>
</td><tr><td>
Albert Motillo</td><td>GE</td><td>Parsing CT, Detection</td><td></td><td>
</td><tr><td>
Simrin Nagpal</td><td>Queens University</td><td>CT/US registration</td><td></td><td>
</td><tr><td>
Samon Nuranian</td><td>UBC</td><td>US-guided intervension, spine</td><td></td><td>
</td><tr><td>
Andre Remi</td><td>UCLA</td><td>Longitudinal changes in TBI, tissue types</td><td></td><td>
</td><tr><td>
Peter Risholm</td><td>BWH</td><td>Brain, head and neck, radiation therapy</td><td>Probabilistic Uncertainty</td><td>
</td><tr><td>
Samira Sojoudi</td><td>UBC</td><td>Spine, CT/US registration</td><td></td><td>
</td><tr><td>
Matthew Toews</td><td>BWH</td><td>General registration</td><td>SIFT landmark correspondence</td><td>
</td><tr><td>
Bo Wang</td><td>Utah</td><td>TBI image segmentation</td><td></td><td>
</td><tr><td>
Kevin Wang</td><td>Princess Margaret Hospital</td><td>Adaptive radiation therapy, longitudinal</td><td></td><td>
</td><tr><td>
William Wells</td><td>BWH</td><td>Interventional applications</td><td>Theory: Segmentation, Registration</td><td></td>
<table>

== Links for Data ==
* [http://www.matthewtoews.com/namic2012 Matt's initial examples]
* [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:RegLibTable Slicer Registration Case Library]
* [http://dmip1.rad.jhmi.edu/xcat/ XCAT]
* [http://wiki.na-mic.org/Wiki/index.php/File:EnlargedLVCase_Normal.zip DTI Files Enlarged LV registration with normal control]
* [http://wiki.na-mic.org/Wiki/index.php/File:Krabbe_Controls_DWI.zip DWI Files Enlarged LV registration with normal control]
* [http://www.na-mic.org/Wiki/index.php/DBP3:UCLA#Data TBI Cases]
* [http://www.nitrc.org/projects/tumorsim/ TumorSim] longitudinal data: To appear at http://midas3.kitware.com

== Links for Tools & Methods ==
* Sliding Geometries Registration: http://public.kitware.com/Wiki/TubeTK
* Geometric Metamorphosis: https://github.com/calaTK/calaTK

== Links for Papers ==
* Sliding Geometries
** ISBI 2011: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3141338/
** Abdominal Imaging, MICCAI, 2011: http://www.springerlink.com/content/552824638l375645/
* Geometric MetaMorphosis
** MICCAI 2011: http://www.springerlink.com/content/7r077665012078r5/

</div>

File:TBI Slicer-BRAINS BSpline.gif

2012-06-20T21:21:47Z

Meier:

2012 Summer Project Week:DifficultRegistration

2012-06-20T20:15:49Z

Meier: /* Delivery Mechanism */

__NOTOC__
<gallery>
Image:PW-MIT2012.png|[[2012_Summer_Project_Week#Projects|Projects List]]
Image:Ct-body-atlas.jpg
Image:Ct-body-cropped.jpg
Image:Ct-body-legs.jpg
Image:Mr-brain-atlas.jpg
Image:Mr-brain-tbi.jpg
Image:Mr-brain-rotated.jpg
Image:Mr-brain-rhesus.jpg
</gallery>

==Key Investigators==
* Erasmus Medical Center: Stefan Klein
* University College London: Marc Modat
* UNC: Aditya Gupta, Martin Styner
* BWH: Matthew Toews, Petter Risholm, Dominik Meier, William Wells

<div style="margin: 20px;">
<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Objective</h3>
To identify solutions to difficult image registration problems that challenge the limits of current technology. Aspects of difficulty will include:
<ul>
<li>inter-subject registration
<li>truncation, missing tissue
<li>unknown initialization
<li>inter-species registration
<li>articulated deformation
</ul>
</div>

<div style="width: 27%; float: left; padding-right: 3%;">

<h3>Approach, Plan</h3>
A set of difficult pair-wise registration problems will be considered. Participants will discuss workable solutions based on their expertise and background, and these solutions will be documented.
<br>
Registration cases can be found [http://www.matthewtoews.com/namic2012 here].
</div>

<div style="width: 40%; float: left;">

<h3>Progress</h3>TBA

</div>
</div>

<div style="width: 97%; float: left;">

==Delivery Mechanism==
<b>Attention Participants:</b> Please log in and update/correct entries in the table below. For bonus points, please provide links or solutions to image registration problems on this page.<br>
<table border="1">
<th>Participant</th><th>Affiliation</th><th>Context</th><th>Techniques</th><th>Solutions/Links
</th><tr><td>
Steven Aylward</td><td>Kitware</td><td>CT, US, ressection, brain tumors, changing pathology, sliding organ</td><td>Sliding Geometry, Geometric Metamorphosis</td><td>
</td><tr><td>
Karl Diedrich</td><td>AZE</td><td>Rigid registration, abdomen</td><td>Multi-resolution registration</td><td>
</td><tr><td>
James Fishbaugh</td><td>SCI</td><td>Shape analysis and registration</td><td></td><td>
</td><tr><td>
Aditya Gupta</td><td>UNC</td><td>DTI, enlarged lateral ventricles</td><td></td><td>
</td><tr><td>
Stefan Klein</td><td>Erasmus Medical Center</td><td>General Registration</td><td></td><td>
</td><tr><td>
Ivan Kolesov</td><td>Georia Tech</td><td>Articulated, point-based registration</td><td></td><td>
</td><tr><td>
Dominik Meier</td><td>BWH</td><td>General registration</td><td>Slicer: BRAINS</td><td>
[[Image:IntraOp_Slicer-BRAINS_BSpline.gif|60px|lleft|IntraOp via BRAINS]]</td><tr><td>
Marc Modat</td><td>UCL</td><td>Intra-op, longitudinal</td><td>NiftiReg</td><td>
</td><tr><td>
Albert Motillo</td><td>GE</td><td>Parsing CT, Detection</td><td></td><td>
</td><tr><td>
Simrin Nagpal</td><td>Queens University</td><td>CT/US registration</td><td></td><td>
</td><tr><td>
Samon Nuranian</td><td>UBC</td><td>US-guided intervension, spine</td><td></td><td>
</td><tr><td>
Andre Remi</td><td>UCLA</td><td>Longitudinal changes in TBI, tissue types</td><td></td><td>
</td><tr><td>
Peter Risholm</td><td>BWH</td><td>Brain, head and neck, radiation therapy</td><td>Probabilistic Uncertainty</td><td>
</td><tr><td>
Samira Sojoudi</td><td>UBC</td><td>Spine, CT/US registration</td><td></td><td>
</td><tr><td>
Matthew Toews</td><td>BWH</td><td>General registration</td><td>SIFT landmark correspondence</td><td>
</td><tr><td>
Bo Wang</td><td>Utah</td><td>TBI image segmentation</td><td></td><td>
</td><tr><td>
Kevin Wang</td><td>Princess Margaret Hospital</td><td>Adaptive radiation therapy, longitudinal</td><td></td><td>
</td><tr><td>
William Wells</td><td>BWH</td><td>Interventional applications</td><td>Theory: Segmentation, Registration</td><td></td>
<table>

== Links for Data ==
* [http://www.matthewtoews.com/namic2012 Matt's initial examples]
* [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:RegLibTable Slicer Registration Case Library]
* [http://dmip1.rad.jhmi.edu/xcat/ XCAT]
* [http://wiki.na-mic.org/Wiki/index.php/File:EnlargedLVCase_Normal.zip Enlarged LV registration with normal control]
* [http://www.na-mic.org/Wiki/index.php/DBP3:UCLA#Data TBI Cases]
* [http://www.nitrc.org/projects/tumorsim/ TumorSim] longitudinal data: To appear at http://midas3.kitware.com

== Links for Tools & Methods ==
* Sliding Geometries Registration: http://public.kitware.com/Wiki/TubeTK
* Geometric Metamorphosis: https://github.com/calaTK/calaTK

== Links for Papers ==
* Sliding Geometries
** ISBI 2011: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3141338/
** Abdominal Imaging, MICCAI, 2011: http://www.springerlink.com/content/552824638l375645/
* Geometric MetaMorphosis
** MICCAI 2011: http://www.springerlink.com/content/7r077665012078r5/

</div>

File:IntraOp Slicer-BRAINS BSpline.gif

2012-06-20T20:13:12Z

Meier:

2012 Summer Project Week:DifficultRegistration

2012-06-18T19:49:59Z

Meier:

Projects:RegistrationDocumentation:RegLibTable

2012-06-12T20:14:52Z

Meier:

[[Projects:RegistrationDocumentation:UseCaseInventory|back to Library Main Page]] <br>

= Registration Library Cases : Sortable Table =
to link to the library case page, click on the thumbnail image, to link to the toolbox documentation, click on the link in the toolbox column. To sort the table by a category, click on the sort icon in the column header.<br>
Legend:
:*[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]<small> this case is up to date for version '''4.1'''</small> <br>
:*[[Image:Slicer_cvers_banner.png‎|60px|this case is up to date for version '''3.6.3''']]<small> this case is up to date for version '''3.6.3'''</small> <br>
:*[[Image:Slicer3-6Announcement-v1.png‎‎|60px| this case is up to date for version 3.6.1]]<small> this case is up to date for version 3.6.1</small><br>
:*[[Image:UnderConstruction_xparent.png‎|60px| these cases are not yet registered / under development]]<small> these cases are not yet registered / under development or presented as "challenge" cases for which no solution is avail. with the current Slicer tools. Some of these may have solutions with developer/extension modules or methods under development. Please contact the [mailto:slicer-users@bwh.harvard.edu Slicer-User List] for inquiries.</small><br>

{| class="wikitable sortable labelpage labelpagetable" border="1"
|-
! id
! thumbnail
! structure
! pathology
! DOF
! toolbox
! modality
! description
! status
|-
| 1
| [[Image:RegUC2_thumb_t0.png|60px|lleft|RegLib C01: Tumor change assessment|link=Projects:RegistrationLibrary:RegLib_C01]]
| brain
| meningioma
| 12
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| MRI T1
| change detection, tumor follow-up
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 2
|[[Image:RLib02_SPGR.png|60px|lleft|RegLib C02: MS multispectral alignment|link=Projects:RegistrationLibrary:RegLib_C02]]
| brain
| multiple sclerosis
| 12
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI T2 FLAIR
|
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 3
| [[Image:RegLib_C03_DTIVol_axial.png|60px|lleft|RegLib C03: DTI alignment|link=Projects:RegistrationLibrary:RegLib_C03]]
| brain
| tumor
| nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:DeformableB-SplineRegistration-Documentation-3.6 Fast Nonrigid BSpline]
| DTI
| align DTI volume with structural reference scan (T2)
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 4
| [[Image:Reglib_C04_Thumb_PD1.jpg‎|60px|lleft|RegLib C04: MS Lesion baseline|link=Projects:RegistrationLibrary:RegLib_C04]]
| Brain
| multiple sclerosis
| 12
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit] or [http://www.slicer.org/slicerWiki/index.php/Modules:RegisterImages-Documentation-3.6 Expert Automated]
| MRI PD/T2 T1Gd
| align 2 sets of multi-contrast MRI for lesion change assessment
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 5
| [[Image:RegLib C05 KneeMRI1.png|60px|lleft|RegLib 05: Knee MRI subject 1|link=Projects:RegistrationLibrary:RegLib_C05]]
| knee
| N/A
| 12
| [http://www.slicer.org/slicerWiki/index.php/Modules:PythonSurfaceICPRegistration-Documentation-3.6 Surface Registration]
| MRI
| inter-subject alignment of knee MRI for atlas-based segmentation
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 6
| [[Image:RegLib C06 BreastMRIPostRx.png|60px|lleft|RegLib 06: Breast MRI|link=Projects:RegistrationLibrary:RegLib_C06]]
| breast
| tumor
| 12 + nonrigid
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| MRI
| post-intervention assessment of breast cancer
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 7
| [[Image:RegLib C07_Thumb1.png|60px|lleft|RegLib 07: Prostate baseline|link=Projects:RegistrationLibrary:RegLib_C07]]
| prostate
| N/A
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| change-assessment in post-intervention MRI follow-up
| [[Image:Slicer_cvers_banner.png|left|70px|This case is complete and up to date for version 3.6.3]]
|-
| 8
| [[Image:RegLib_C08_WholeBodyPET-CT1.png|60px|lleft|RegLib C08: PET-CT1|link=Projects:RegistrationLibrary:RegLib_C08]]
| abdominal, thoracic
| path
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:AffineRegistration-Documentation-3.6 Fast Affine] + [http://www.slicer.org/slicerWiki/index.php/Modules:DeformableB-SplineRegistration-Documentation-3.6 Fast Nonrigid BSpline] or [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| PET-CT
| follow-up change assessment from combined whole-body PET-CT pair
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 9
| [[Image:RegLib_C09_Thumb2.png|70px|lleft|RegLib C09: T1 SPGR|link=Projects:RegistrationLibrary:RegLib_C09]]
| brain
| infarct
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| fMRI
| align fMRI with structural reference (T1)
| [[Image:Slicer_cvers_banner.png|70px|This case is complete and up to date for version 3.6.3]]
|-
| 10
| [[Image:RegLib_C10_EMAtlas2.png|60px|lleft|Probabilistic Tissue Atlas|link=Projects:RegistrationLibrary:RegLib_C10]]
| brain
| N/A
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:AffineRegistration-Documentation-3.6 Fast Affine] + [http://www.slicer.org/slicerWiki/index.php/Modules:DeformableB-SplineRegistration-Documentation-3.6 Fast Nonrigid BSpline]
| MRI
| align probabilistic tissue atlas with target brain for guiding EM tissue class segmentation
| [[Image:Slicer3-6Announcement-v1.png‎|70px|This case is complete and up to date for version 3.6.1]]
|-
| 11
| [[Image:RegLib_C11_AtlasMerge_1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C11]]
| brain
| none
| 12
| [http://www.slicer.org/slicerWiki/index.php/Modules:PythonSurfaceICPRegistration-Documentation-3.6 Surface Registration]
| MRI / labelmaps
| co-register surface models of thalamus for two separate subjects, merging anatomical labelmaps
| [[Image:Slicer3-6Announcement-v1.png‎|70px|This case is complete and up to date for version 3.6.1]]
|-
| 12
| [[Image:RegLib_C12_LiverTumor_MRI.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C12]]
| liver
| tumor
| nonrigid
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| MRI + CT
| Liver tumor ablation #1: intra-operative MRI to pre-op CT.
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
|-
| 13
| [[Image:RegLib_C13_LiverTumor2_CTpost.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C13]]
| liver
| tumor
| nonrigid
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| CT + MRI
| Liver tumor ablation : post-operative CT to pre-op CT & MRI
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 14
| [[Image:RegLib_C14_Thumb_PET.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C14]]
| brain
| N/A
| 12
| [http://www.slicer.org/slicerWiki/index.php/Modules:RegisterImages-Documentation-3.6 Expert Automated] or [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| PET + MRI
| alignment of brain PET to structural MRI, with adjustments to MRI aspect ratio and orientation.
| [[Image:Slicer3-6Announcement-v1.png‎|70px|This case is complete and up to date for version 3.6.1]]
|-
| 15
| [[Image:RegLib_C15_Thumb.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C15]]
| brain
| none
| 6
| [http://www.slicer.org/slicerWiki/index.php/Modules:ACPCTransform-Documentation-3.6 AC-PC Transform]
| MRI
| Realigning a single brain MRI along the anterior-posterior commissure line.
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 16
| [[Image:RegLib_C16_Brain0.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C16]]
| brain
| N/A
| 6
| [http://www.slicer.org/slicerWiki/index.php/Modules:Transforms-Documentation-3.6 Manual Registration:Transforms]
| MRI
| manually align FLAIR MRI with anatomical reference T1.
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 17
| [[Image:RegLib_C17_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C17]]
| kidney
| tumor
| affine
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| CT + MRI
| kidney tumor ablation : intra-operative CT to pre-op MRI
| [[Image:Slicer_cvers_banner.png‎|60px|this case is up to date for version '''3.6.3''']]
|-
| 18
| [[Image:RegLib_C18_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C18]]
| brain
| healthy, aging
| 12
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| align brain MRI both across and within exams
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 19
| [[Image:RegLib_C19_thumb_all.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C19]]
| brain
| healthy
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit] & [http://www.slicer.org/slicerWiki/index.php/Modules:DeformableB-SplineRegistration-Documentation-3.6 Fast nonrigid BSpline]
| MRI
| multi-stage inter- and intra-subject MRI registration
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 20
| [[Image:RegLib_C20_Thumb1.png|60px|lleft|RegLib C20: PET-CT|link=Projects:RegistrationLibrary:RegLib_C20]]
| abdominal, thoracic
| N/A
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| PET-CT
| follow-up change assessment from combined whole-body PET-CT pair
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 21
| [[Image:RegLib_C21_Thumb1.png|60px|lleft|RegLib C21: knee MRI|link=Projects:RegistrationLibrary:RegLib_C21]]
| knee
| N/A
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| inter-subject knee registration to build priors for cartilage segmentation
| [[Image:Slicer_cvers_banner.png‎|60px|this case is up to date for version '''3.6.3''']]
|-
| 27
| [[Image:RegLib27_DTI.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C27]]
| brain
| tumor
| 12 + nonrigid
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| DTI
| Alignment of DTI scan to structural reference T1-SPGR for surgical planning (tumor resection)
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 28
| [[Image:RegLib_C28_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C28]]
| vertebra
| spine cancer
| 12
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| CT
| Alignment of in vitro CT of spinal vertebra before and after damage
| [[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 29
| [[Image:RegLib_C29_Thumb.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C29]]
| brain
| tumor
| 12 + nonrigid
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| DTI
| Alignment of DTI scan to structural reference T2/T1-SPGR for surgical planning (tumor resection)
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 30
| [[Image:RegLib_C30_Thumb3.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C30]]
| brain
| N/A
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| DTI
| Alignment of DTI scan to structural reference T1 direct. No T2 available.
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 31
| [[Image:RegLib_C31_Thumb6.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C31]]
| brain
| TBI
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| intra- and inter-exam registration of multi-contrast MRI follow-up in TBI
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 32
| [[Image:RegLib_C30_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C30]]
| brain
| N/A
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| DTI
| Alignment of DTI scan: inverse direction: aligning structural reference to DTI.
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 33
| [[Image:RegLib_C33_Thumb4.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C33]]
| brain
| N/A
| 12 + nonrigid
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| DTI
| Alignment of hi-res multi contrast exam, incl. T1Gd FLAIR and DTI to T1 reference
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 34
| [[Image:RegLib_C34_Thumb2.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C34]]
| animal
| N/A
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| Alignment of mouse brain MRI atlas or different age
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 35
| [[Image:RegLibC35_Thumb2.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C35]]
| animal
| N/A
| 12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:SurfaceRegistration Surface Registration]
| MRI
| Alignment of mouse colon MRI
| [[Image:UnderConstruction_xparent.png|40px|left|This is a challenge case / currently unsolved]]
|-
| 37
| [[Image:RegLib_C37_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C37]]
| brain
| tumor
| 6+12 + nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| Alignment of intra-subject MRI for therapy assessment
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.1]]
|-
| 38
| [[Image:RegLib_C38_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C38]]
| brain
| TBI
| 12 + nonrigid
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| MRI
| intra- and inter-exam registration of multi-contrast MRI follow-up in TBI at 3T
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
| 39
| [[Image:RegLib_C39_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C39]]
| vertebra
| spine cancer
| 12
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| CT
| Alignment of in vitro CT of thoracic vertebra before and after damage
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.3]]
|-
| 40
| [[Image:RegLib_C40_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C40]]
| wood sample
| materials science
| 12+nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| CT
| Alignment of in micro CT of wood samples to test hygromechanical behavior.
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.3]]
|-
| 41
| [[Image:RegLib_C41_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C41]]
| Mouse Brain
|
| 12+nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| Alignment of mouse brain MRI for group comparison
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.3]]
|-
| 42
| [[Image:RegLib_C42_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C42]]
| Infant Brain
| Autism
| 12+nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| Alignment of in longitudinal MRI of infant with autism (2-4 years)
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.3]]
|-
| 43
| [[Image:RegLib_C43_Thumb1b.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C43]]
| vertebrae/spine
| cancer
| rigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:PythonSurfaceICPRegistration-Documentation-3.6 Surface Registration]
| CT/3D models
| Analysis of structural integrity change
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.4]]
|-
| 44
| [[Image:RegLib_C44_Thumb1.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C44]]
| Pelvis
| N/A
| 12+nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| CT
| Analysis of inter-subject shape differences via nonrigid deformation/registration
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.3]]
|-
| 46
| [[Image:RegLib_C46_Thumb2.gif|60px|left|link=Projects:RegistrationLibrary:RegLib_C46]]
| dynamic lung MRI
|
| nonrigid
| [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
| MRI
| Alignment of serial 2D lung MRI to assess dynamics
| [[Image:Slicer3-6Announcement-v1.png‎|70px|left|This case is complete and up to date for version 3.6.3]]
|-
| 47
| [[Image:RegLib_C12_LiverTumor_MRI.png|60px|left|link=Projects:RegistrationLibrary:RegLib_C47]]
| liver
| tumor
| nonrigid
| [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)]
| MRI + CT
| Liver tumor ablation: intra-op MRI to intra-op CT.
| 4[[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]]
|-
|}

Projects:RegistrationDocumentation:UseCaseInventory:BrainIntraMRI

2012-06-12T20:14:26Z

Meier:

[[Projects:RegistrationDocumentation:UseCaseInventory|back to Library Main Page]] <br>

==Registration Case Inventory Brain==
*[[Image:RegUC2_thumb_t0.png|70px|lleft|RegLib C01: Tumor change assessment]] [[Image:RegUC2_thumb_t1.png|70px|lleft|RegLib C01: Tumor change assessment]][[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]] '''Case 01: [[Projects:RegistrationLibrary:RegLib_C01|Intra-subject Brain MRI (Tumor growth assessment); ''' axial T1 with meningioma]]
*[[Image:RLib02_SPGR.png|70px|lleft|RegLib C02: MS multispectral alignment]] [[Image:RLib02_FLAIR_150.png|70px|lleft|RegLib C02: MS multispectral alignment]] [[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]] '''Case 02: [[Projects:RegistrationLibrary:RegLib_C02|Intra-subject Brain MRI (Multiple Sclerosis); ''' T2 FLAIR to (defaced) T1 SPGR]]
*[[Image:Reglib_C04_Thumb_PD1.jpg‎|70px|lleft|RegLib C04: MS Lesion baseline]] [[Image:Reglib_C04_Thumb_PD2.jpg‎|70px|lleft|RegLib C04: MS Lesion follow-up]] [[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]] '''Case 04: [[Projects:RegistrationLibrary:RegLib_C04|Intra-subject Brain MRI (Multiple Sclerosis).''' Aligning multiple follow-up exams of MS MRI for lesion change assessment ]]
*[[Image:RegLib_C15_Thumb.png|70px|lleft|RegLib C15: AC-PC alignment]] [[Image:RegLib_C15_Thumb.png‎|70px|lleft|RegLib C15: AC-PC alignment]]'''Case 15: [[Projects:RegistrationLibrary:RegLib_C15|Brain MRI reorientation along AC-PC line.''' Realigning a single brain MRI along the anterior-posterior commissure line]]
*[[Image:RegLib_C16_Brain0.png|70px|lleft|RegLib C16: Manual alignment]] [[Image:RegLib_C16_Brain1.png‎|70px|lleft|RegLib C16: Manual alignment]]'''Case 16: [[Projects:RegistrationLibrary:RegLib_C16|Manual alignment of multi-contrast brain MRI.''' manually align FLAIR MRI with anatomical reference T1]]

*[[Image:RegLib_C18_Thumb1.png|70px|lleft|RegLib C18]] [[Image:RegLib_C18_Thumb2.png‎|70px|lleft|RegLib C18]] [[Image:Slicer3-6Announcement-v1.png‎|70px|This case is complete and up to date for version 3.6.1]] '''Case 18: [[Projects:RegistrationLibrary:RegLib_C18|Multi-contrast brain MRI in Longitudinal Aging Study''' align FLAIR,T1 and T2 exams within '''and''' across exams]]
*[[Image:RegLib_C31_Thumb1.png|70px|lleft|RegLib C31]] [[Image:RegLib_C31_Thumb6.png‎|70px|lleft|RegLib C31]] [[Image:Slicer3-6Announcement-v1.png‎|70px|This case is complete and up to date for version 3.6.1]] '''Case 31: [[Projects:RegistrationLibrary:RegLib_C31|severe TBI MRI follow-up''' align acute and follow-up of FLAIR,contrast,T2 and DWI exams to reference; both intra- and inter-exam registration, incl. nonrigid for inter-exam]]
*[[Image:RegLib_C37_Thumb1.png|70px|lleft|RegLib C37]] [[Image:RegLib_C37_Thumb2.png‎|70px|lleft|RegLib C37]] [[Image:Slicer3-6Announcement-v1.png‎|70px|This case is complete and up to date for version 3.6.1]] '''Case 37: [[Projects:RegistrationLibrary:RegLib_C37|MRI brain tumor follow-up''' align acute and follow-up of T1 exams incl. nonrigid for change detection]]
*[[Image:RegLib_C38_Thumb1.png|70px|lleft|RegLib C38]] [[Image:RegLib_C38_Thumb6.png‎|70px|lleft|RegLib C38]] [[Image:Slicer41VerifiedIcon.png|50px|verified/updated for Slicer 4.1]] '''Case 38: [[Projects:RegistrationLibrary:RegLib_C38|severe TBI MRI follow-up at 3T''' align acute and follow-up of FLAIR,contrast,T2 and SWI exams to reference; incl. nonrigid for inter-exam]]
*[[Image:RegLib_C42_Thumb1.png|70px|lleft|RegLib C42]] [[Image:RegLib_C42_Thumb2.png‎|70px|lleft|RegLib C42]] [[Image:Slicer3-6Announcement-v1.png‎|70px|This case is complete and up to date for version 3.6.1]] '''Case 42: [[Projects:RegistrationLibrary:RegLib_C42|longitudinal follow-up of infant MRI in Autism]]

Projects:RegistrationLibrary:RegLib C04

2012-06-12T20:14:00Z

Meier:

[[Projects:ARRASuplements|Back to ARRA main page]] <br>
[[Projects:RegistrationDocumentation|Back to Registration main page]] <br>
[[Projects:RegistrationDocumentation:UseCaseInventory|Back to Registration Use-case Inventory]] <br>

= <small>updated for '''v4.1'''</small> [[Image:Slicer4_RegLibLogo.png|150px]] <br> Slicer Registration Library Case 04: Multi-contrast brain MRI of Multiple Sclerosis =
=== Input ===
{| style="color:#bbbbbb; " cellpadding="10" cellspacing="0" border="0"
|[[Image:Reglib_C04_Thumb_PD1.jpg|100px|lleft|this is the main fixed reference image. All images are ev. aligned into this space]]
|[[Image:Reglib_C04_Thumb_T21.jpg|100px|lleft|this is the main fixed reference image. All images are ev. aligned into this space]]
|[[Image:RegArrow_Affine.png|70px|lleft]]
|[[Image:Reglib_C04_Thumb_Gd1.jpg|100px|lleft|this is the intra-subject moving image. ]]
|-
|exam 1: PD
|exam 1: T2
|
|exam 1: T1-Gd
|-
|[[Image:RegArrow_AffineVert.png|70px|lleft]]
|
|
|
|-
|[[Image:Reglib_C04_Thumb_PD2.jpg|100px|lleft|this is the inter-subject moving image, but also the reference for exam 2]]
|[[Image:Reglib_C04_Thumb_T22.jpg|100px|lleft|this is the inter-subject moving image, but also the reference for exam 2]]
|[[Image:RegArrow_Affine.png|70px|lleft]]
|[[Image:Reglib_C04_Thumb_Gd2.jpg|100px|lleft|this is the moving image. ]]
|-
|exam 2: PD
|exam 2: T2
|
|exam 2: T1-Gd
|}

=== Slicer 4.1 recommended Modules ===
*[http://www.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit BrainsFit]
*tutorials here are for the above module, but you may also use the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/AffineRegistration Affine Registration] or [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/ExpertAutomatedRegistration Expert Automated Registration] modules.

===Objective / Background ===
This scenario occurs in many forms whenever we wish to assess change in a series of multi-contrast MRI. The follow-up scan(s) are to be aligned with the baseline, but also the different series within each exam need to be co-registered, since the subject may have moved between acquisitions. Hence we have a set of nested registrations. This particular exam features a dual echo scan (PD/T2), where the two structural scans are aligned by default. The post-contrast T1-GdDTPA scan however is not necessarily aligned with the dual echo. Also the post-contrast scan is taken with a clipped field of view (FOV) and a lower axial resolution, with 4mm slices and a 1mm gap (which we treat here as a de facto 5mm slice).
[[Projects:RegistrationLibrary:RegLib_C04:About| read more about this dataset here]]

=== Download ===
*Data:
**[[Media:RegLib_C04_Data.zip‎|'''Registration Library Case 04: MS Multi-contrast series (PD,T2, T1-GdDTPA): Lesion change assessment''' <small> (Data & Solution Xforms, zip file 18 MB) </small>]]
*Documentation
**[[Media:RegLib_C04_Register_interExam.mov‎|ScreenCast Video: loading data & inter-exam registration: aligning exam 2 to exam 1 <small> (quicktime movie, 8 MB) </small>]]
**[[Media:RegLib_C04_Register_intraExam.mov‎|ScreenCast Video: intra-exam registration: aligning T1Gd of exam 2 to PD of exam 2 <small> (quicktime movie, 8 MB) </small>]]
**[[Media:RegLib_C04_Register_XformHierarchy.mov‎|ScreenCast Video: transform hierarchy: how to arrange the MRML data tree to properly reflect the mutual dependencies of transforms <small> (quicktime movie, 2 MB) </small>]]

=== Keywords ===
MRI, brain, head, intra-subject, multiple sclerosis, MS, multi-contrast, change assessment, dual echo, nested registration

===Input Data===
*reference/fixed : PD.1 baseline exam , 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition, RAS orientation.
*fixed T2.1 baseline exam , 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition, RAS orientation. -> (aligned with PD.1, not used for registering)
*moving: T1.1 (GdDTPA contrast-enhanced scan) baseline exam 0.9375 x 0.9375 x 5 mm voxel size, axial acquisition.
*moving: PD.2 follow-up exam 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition.
*moving: T2.2 follow-up exam 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition. -> same orientation as PD2, will have same transform applied
*moving:T1.2-GdDTPA follow-up exam0.9375 x 0.9375 x 5 mm voxel size, axial acquisition. -> undergoes 2 transforms: first to PD.2, then to PD.1

===Registration Challenges===
*we have multiple nested transforms: each exam is co-registered within itself, and then the exams are aligned to eachother
*potential pathology change can affect the registration
*anisotropic voxel size causes difficulty in rotational alignment
*clipped FOV and low tissue contrast of the post-contrast scan

===Key Strategies===
*we first register the post-contrast scans within each exam to the PD
*second we register the follow-up PD scan to the baseline PD
*we also move the T2 exam within the same Xform
*we then nest the first alignment within the second
*because of the contrast differences and anisotropic resolution we use Mutual Information as cost function for better robustness
=== Procedure ===
*there is a brief movie in the download section that shows this procedure step by step. Guides below use the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)] module, but you may also use the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/AffineRegistration Affine Registration] or [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/ExpertAutomatedRegistration Expert Automated Registration] modules.
*'''Phase 1''': register inter-exam exam 2 -> exam 1
#open the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS) module]
##''Fixed Image Volume'': e1_PD
##''Moving Image Volume'': e2_PD
##Output Settings:
###''Slicer BSpline Transform": none
###''Slicer Linear Transform'': create & rename new transform: Xf1_e21_Affine.tfm
###''Output Image Volume'': none
##''Registration Phases'': check boxes for ''Rigid'' and ''Affine''
##''Main Parameters''
###'''Number of Samples''': 200,000
##click: Apply; runtime < 1 min (MacPro QuadCore 2.4GHz)
#note that the Slicer4.1 version of BRAINS registration does '''not''' automatically place the moving volume inside the result transform, as it did for Slicer 3.6. In order to see the result, you must either go to the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/Data ''Data module''] and drag the moving volume inside the transform node, or select to generate a resampled ''Output Volume'', as done above. The demo movie you can download here shows how to do this.
*'''Phase 2''': register intra-examT1Gd to PD
#open the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS) module]
##''Fixed Image Volume'': e1_PD
##''Moving Image Volume'': e1_T1Gd
##Output Settings:
###''Slicer BSpline Transform": none
###''Slicer Linear Transform'': create & rename new transform: Xf2_e1-T1Gd_Rigid.tfm
###''Output Image Volume'': none
##''Registration Phases'': check boxes for ''Rigid'' only
##''Main Parameters''
###'''Number of Samples''': 200,000
##click: Apply; runtime < 1 min (MacPro QuadCore 2.4GHz)
#note that the Slicer4.1 version of BRAINS registration does '''not''' automatically place the moving volume inside the result transform, as it did for Slicer 3.6. In order to see the result, you must either go to the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/Data ''Data module''] and drag the moving volume inside the transform node, or select to generate a resampled ''Output Volume'', as done above. The demo movie you can download here shows how to do this.
#repeat for exam 2, i.e
##''Fixed Image Volume'': e2_PD
##''Moving Image Volume'': e2_T1Gd
##''Slicer Linear Transform'': create & rename new transform: Xf3_e2-T1Gd_Rigid.tfm
*'''Phase 3''': organize transform hierarchies in the ''Data'' tree
#go to the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/Data ''Data module'']
##drag the volume node e1_T1Gd onto the transform Xf2_e1-T1Gd_Rigid; let go of the mouse button when you see a hilight box appear around the transform node name
##drag the volume node e2_T1Gd onto the transform Xf3_e2-T1Gd_Rigid;
##drag the volume node e2_PD and e2_T2 onto the transform Xf1_e21_Affine.tfm
##drag the transform node Xf3_e2_T1Gd_Rigid.tfm onto the transform Xf1_e21_Affine.tfm
##your MRML data tree should look like the image on the right
##different images into fore- and background, respectively, and use the fade slider to shift between fore- and background to view the registration quality. You can also use OPTION+CMD key and drag the mouse to fade between back- and foreground.
#to apply the transform and lock in the new position, right click on the volume and select ''Harden Transform'' from the popup menu. The node will move back out to the main level. Note that this applies the transform to the physical orientation info in the image header and does not actually perform a resampling. It is recommended to not apply resampling until the very end of an analysis pipeline, to avoid interpolation-related data loss. To perform a resampling follow steps below:
*'''Phase 4''': Resampling (optional)
#go to [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSResample ''Resample Image (BRAINS)'' module] (in the Registration menu)
##''Image To Warp'': e2_PD
##''Reference Image'': e1_PD
##''Output Image'': create new & rename: e2_PD_Xf1
##''Pixel Type'': ushort
##''Warp By Transform'': Xf1_e21_Affine created in Phase I above
##''Interpolation Mode'': '''linear'''
#note to avoid multiple resampling, combine the two nested transforms for the two volumes before performing the resampling step above. Alternatively you can execute the ''Harden Transform'' step above first and then resample the volume after, by giving no transform (i.e. resampling in place) but listing the fixed image (e.g. e1_PD) as reference. This will resample the moving image into the same representation as the reference.
before registration: [[Image:RegLib_C04_DataTree.png|200px|Orig. MRML Data tree]]
after registration: [[Image:RegLib_C04_DataTree2.png|200px|Registered. MRML Data tree: exam 2 is within nested affine transforms]]

=== Registration Results===
[[Image:RegLib_C04_T1Gd-PD_unreg_AnimGif.gif||500px|Unregistered baseline data: PD vs. T1Gd]] Unregistered baseline data: PD vs. T1Gd<br>
[[Image:RegLib_C04_PDunreg_AnimGif.gif||500px|Unregistered followup data: PD exam 2 vs. exam 1]] Unregistered followup data: PD exam 2 vs. exam 1<br>
[[Image:RegLib_C04_T1Gd1-PD1_reg_AnimGif.gif|500px|Registered baseline data]] Registered baseline data <br>
[[Image:RegLib_C04_PDreg_AnimGif.gif|500px|Registered followup data]] Registered followup data<br>
[[Image:RegLib_C04_3DLesionChange_AnimGif.gif|200px|Lesion change visualization in 3D]]Lesion change visualization in 3D<br>
[[Image:RegLib_C04_PDSubtraction.png‎|500px|Lesion change via subtraction imaging of co-registered PD]]Lesion change via subtraction imaging of co-registered PD

Projects:RegistrationLibrary:RegLib C04

2012-06-12T20:13:28Z

Meier: /* Slicer 4.1 recommended Modules */

[[Projects:ARRASuplements|Back to ARRA main page]] <br>
[[Projects:RegistrationDocumentation|Back to Registration main page]] <br>
[[Projects:RegistrationDocumentation:UseCaseInventory|Back to Registration Use-case Inventory]] <br>

= <small>v3.6.3</small> [[Image:Slicer_cvers_banner.png|150px]] Slicer Registration Library Case 04: Multi-contrast brain MRI of Multiple Sclerosis =
=== Input ===
{| style="color:#bbbbbb; " cellpadding="10" cellspacing="0" border="0"
|[[Image:Reglib_C04_Thumb_PD1.jpg|100px|lleft|this is the main fixed reference image. All images are ev. aligned into this space]]
|[[Image:Reglib_C04_Thumb_T21.jpg|100px|lleft|this is the main fixed reference image. All images are ev. aligned into this space]]
|[[Image:RegArrow_Affine.png|70px|lleft]]
|[[Image:Reglib_C04_Thumb_Gd1.jpg|100px|lleft|this is the intra-subject moving image. ]]
|-
|exam 1: PD
|exam 1: T2
|
|exam 1: T1-Gd
|-
|[[Image:RegArrow_AffineVert.png|70px|lleft]]
|
|
|
|-
|[[Image:Reglib_C04_Thumb_PD2.jpg|100px|lleft|this is the inter-subject moving image, but also the reference for exam 2]]
|[[Image:Reglib_C04_Thumb_T22.jpg|100px|lleft|this is the inter-subject moving image, but also the reference for exam 2]]
|[[Image:RegArrow_Affine.png|70px|lleft]]
|[[Image:Reglib_C04_Thumb_Gd2.jpg|100px|lleft|this is the moving image. ]]
|-
|exam 2: PD
|exam 2: T2
|
|exam 2: T1-Gd
|}

=== Slicer 4.1 recommended Modules ===
*[http://www.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit BrainsFit]
*tutorials here are for the above module, but you may also use the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/AffineRegistration Affine Registration] or [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/ExpertAutomatedRegistration Expert Automated Registration] modules.

===Objective / Background ===
This scenario occurs in many forms whenever we wish to assess change in a series of multi-contrast MRI. The follow-up scan(s) are to be aligned with the baseline, but also the different series within each exam need to be co-registered, since the subject may have moved between acquisitions. Hence we have a set of nested registrations. This particular exam features a dual echo scan (PD/T2), where the two structural scans are aligned by default. The post-contrast T1-GdDTPA scan however is not necessarily aligned with the dual echo. Also the post-contrast scan is taken with a clipped field of view (FOV) and a lower axial resolution, with 4mm slices and a 1mm gap (which we treat here as a de facto 5mm slice).
[[Projects:RegistrationLibrary:RegLib_C04:About| read more about this dataset here]]

=== Download ===
*Data:
**[[Media:RegLib_C04_Data.zip‎|'''Registration Library Case 04: MS Multi-contrast series (PD,T2, T1-GdDTPA): Lesion change assessment''' <small> (Data & Solution Xforms, zip file 18 MB) </small>]]
*Documentation
**[[Media:RegLib_C04_Register_interExam.mov‎|ScreenCast Video: loading data & inter-exam registration: aligning exam 2 to exam 1 <small> (quicktime movie, 8 MB) </small>]]
**[[Media:RegLib_C04_Register_intraExam.mov‎|ScreenCast Video: intra-exam registration: aligning T1Gd of exam 2 to PD of exam 2 <small> (quicktime movie, 8 MB) </small>]]
**[[Media:RegLib_C04_Register_XformHierarchy.mov‎|ScreenCast Video: transform hierarchy: how to arrange the MRML data tree to properly reflect the mutual dependencies of transforms <small> (quicktime movie, 2 MB) </small>]]

=== Keywords ===
MRI, brain, head, intra-subject, multiple sclerosis, MS, multi-contrast, change assessment, dual echo, nested registration

===Input Data===
*reference/fixed : PD.1 baseline exam , 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition, RAS orientation.
*fixed T2.1 baseline exam , 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition, RAS orientation. -> (aligned with PD.1, not used for registering)
*moving: T1.1 (GdDTPA contrast-enhanced scan) baseline exam 0.9375 x 0.9375 x 5 mm voxel size, axial acquisition.
*moving: PD.2 follow-up exam 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition.
*moving: T2.2 follow-up exam 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition. -> same orientation as PD2, will have same transform applied
*moving:T1.2-GdDTPA follow-up exam0.9375 x 0.9375 x 5 mm voxel size, axial acquisition. -> undergoes 2 transforms: first to PD.2, then to PD.1

===Registration Challenges===
*we have multiple nested transforms: each exam is co-registered within itself, and then the exams are aligned to eachother
*potential pathology change can affect the registration
*anisotropic voxel size causes difficulty in rotational alignment
*clipped FOV and low tissue contrast of the post-contrast scan

===Key Strategies===
*we first register the post-contrast scans within each exam to the PD
*second we register the follow-up PD scan to the baseline PD
*we also move the T2 exam within the same Xform
*we then nest the first alignment within the second
*because of the contrast differences and anisotropic resolution we use Mutual Information as cost function for better robustness
=== Procedure ===
*there is a brief movie in the download section that shows this procedure step by step. Guides below use the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)] module, but you may also use the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/AffineRegistration Affine Registration] or [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/ExpertAutomatedRegistration Expert Automated Registration] modules.
*'''Phase 1''': register inter-exam exam 2 -> exam 1
#open the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS) module]
##''Fixed Image Volume'': e1_PD
##''Moving Image Volume'': e2_PD
##Output Settings:
###''Slicer BSpline Transform": none
###''Slicer Linear Transform'': create & rename new transform: Xf1_e21_Affine.tfm
###''Output Image Volume'': none
##''Registration Phases'': check boxes for ''Rigid'' and ''Affine''
##''Main Parameters''
###'''Number of Samples''': 200,000
##click: Apply; runtime < 1 min (MacPro QuadCore 2.4GHz)
#note that the Slicer4.1 version of BRAINS registration does '''not''' automatically place the moving volume inside the result transform, as it did for Slicer 3.6. In order to see the result, you must either go to the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/Data ''Data module''] and drag the moving volume inside the transform node, or select to generate a resampled ''Output Volume'', as done above. The demo movie you can download here shows how to do this.
*'''Phase 2''': register intra-examT1Gd to PD
#open the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS) module]
##''Fixed Image Volume'': e1_PD
##''Moving Image Volume'': e1_T1Gd
##Output Settings:
###''Slicer BSpline Transform": none
###''Slicer Linear Transform'': create & rename new transform: Xf2_e1-T1Gd_Rigid.tfm
###''Output Image Volume'': none
##''Registration Phases'': check boxes for ''Rigid'' only
##''Main Parameters''
###'''Number of Samples''': 200,000
##click: Apply; runtime < 1 min (MacPro QuadCore 2.4GHz)
#note that the Slicer4.1 version of BRAINS registration does '''not''' automatically place the moving volume inside the result transform, as it did for Slicer 3.6. In order to see the result, you must either go to the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/Data ''Data module''] and drag the moving volume inside the transform node, or select to generate a resampled ''Output Volume'', as done above. The demo movie you can download here shows how to do this.
#repeat for exam 2, i.e
##''Fixed Image Volume'': e2_PD
##''Moving Image Volume'': e2_T1Gd
##''Slicer Linear Transform'': create & rename new transform: Xf3_e2-T1Gd_Rigid.tfm
*'''Phase 3''': organize transform hierarchies in the ''Data'' tree
#go to the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/Data ''Data module'']
##drag the volume node e1_T1Gd onto the transform Xf2_e1-T1Gd_Rigid; let go of the mouse button when you see a hilight box appear around the transform node name
##drag the volume node e2_T1Gd onto the transform Xf3_e2-T1Gd_Rigid;
##drag the volume node e2_PD and e2_T2 onto the transform Xf1_e21_Affine.tfm
##drag the transform node Xf3_e2_T1Gd_Rigid.tfm onto the transform Xf1_e21_Affine.tfm
##your MRML data tree should look like the image on the right
##different images into fore- and background, respectively, and use the fade slider to shift between fore- and background to view the registration quality. You can also use OPTION+CMD key and drag the mouse to fade between back- and foreground.
#to apply the transform and lock in the new position, right click on the volume and select ''Harden Transform'' from the popup menu. The node will move back out to the main level. Note that this applies the transform to the physical orientation info in the image header and does not actually perform a resampling. It is recommended to not apply resampling until the very end of an analysis pipeline, to avoid interpolation-related data loss. To perform a resampling follow steps below:
*'''Phase 4''': Resampling (optional)
#go to [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSResample ''Resample Image (BRAINS)'' module] (in the Registration menu)
##''Image To Warp'': e2_PD
##''Reference Image'': e1_PD
##''Output Image'': create new & rename: e2_PD_Xf1
##''Pixel Type'': ushort
##''Warp By Transform'': Xf1_e21_Affine created in Phase I above
##''Interpolation Mode'': '''linear'''
#note to avoid multiple resampling, combine the two nested transforms for the two volumes before performing the resampling step above. Alternatively you can execute the ''Harden Transform'' step above first and then resample the volume after, by giving no transform (i.e. resampling in place) but listing the fixed image (e.g. e1_PD) as reference. This will resample the moving image into the same representation as the reference.
before registration: [[Image:RegLib_C04_DataTree.png|200px|Orig. MRML Data tree]]
after registration: [[Image:RegLib_C04_DataTree2.png|200px|Registered. MRML Data tree: exam 2 is within nested affine transforms]]

=== Registration Results===
[[Image:RegLib_C04_T1Gd-PD_unreg_AnimGif.gif||500px|Unregistered baseline data: PD vs. T1Gd]] Unregistered baseline data: PD vs. T1Gd<br>
[[Image:RegLib_C04_PDunreg_AnimGif.gif||500px|Unregistered followup data: PD exam 2 vs. exam 1]] Unregistered followup data: PD exam 2 vs. exam 1<br>
[[Image:RegLib_C04_T1Gd1-PD1_reg_AnimGif.gif|500px|Registered baseline data]] Registered baseline data <br>
[[Image:RegLib_C04_PDreg_AnimGif.gif|500px|Registered followup data]] Registered followup data<br>
[[Image:RegLib_C04_3DLesionChange_AnimGif.gif|200px|Lesion change visualization in 3D]]Lesion change visualization in 3D<br>
[[Image:RegLib_C04_PDSubtraction.png‎|500px|Lesion change via subtraction imaging of co-registered PD]]Lesion change via subtraction imaging of co-registered PD

Projects:RegistrationLibrary:RegLib C04

2012-06-12T20:12:55Z

Meier: /* Procedure */

[[Projects:ARRASuplements|Back to ARRA main page]] <br>
[[Projects:RegistrationDocumentation|Back to Registration main page]] <br>
[[Projects:RegistrationDocumentation:UseCaseInventory|Back to Registration Use-case Inventory]] <br>

= <small>v3.6.3</small> [[Image:Slicer_cvers_banner.png|150px]] Slicer Registration Library Case 04: Multi-contrast brain MRI of Multiple Sclerosis =
=== Input ===
{| style="color:#bbbbbb; " cellpadding="10" cellspacing="0" border="0"
|[[Image:Reglib_C04_Thumb_PD1.jpg|100px|lleft|this is the main fixed reference image. All images are ev. aligned into this space]]
|[[Image:Reglib_C04_Thumb_T21.jpg|100px|lleft|this is the main fixed reference image. All images are ev. aligned into this space]]
|[[Image:RegArrow_Affine.png|70px|lleft]]
|[[Image:Reglib_C04_Thumb_Gd1.jpg|100px|lleft|this is the intra-subject moving image. ]]
|-
|exam 1: PD
|exam 1: T2
|
|exam 1: T1-Gd
|-
|[[Image:RegArrow_AffineVert.png|70px|lleft]]
|
|
|
|-
|[[Image:Reglib_C04_Thumb_PD2.jpg|100px|lleft|this is the inter-subject moving image, but also the reference for exam 2]]
|[[Image:Reglib_C04_Thumb_T22.jpg|100px|lleft|this is the inter-subject moving image, but also the reference for exam 2]]
|[[Image:RegArrow_Affine.png|70px|lleft]]
|[[Image:Reglib_C04_Thumb_Gd2.jpg|100px|lleft|this is the moving image. ]]
|-
|exam 2: PD
|exam 2: T2
|
|exam 2: T1-Gd
|}

=== Slicer 4.1 recommended Modules ===
*[http://www.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit BrainsFit]

===Objective / Background ===
This scenario occurs in many forms whenever we wish to assess change in a series of multi-contrast MRI. The follow-up scan(s) are to be aligned with the baseline, but also the different series within each exam need to be co-registered, since the subject may have moved between acquisitions. Hence we have a set of nested registrations. This particular exam features a dual echo scan (PD/T2), where the two structural scans are aligned by default. The post-contrast T1-GdDTPA scan however is not necessarily aligned with the dual echo. Also the post-contrast scan is taken with a clipped field of view (FOV) and a lower axial resolution, with 4mm slices and a 1mm gap (which we treat here as a de facto 5mm slice).
[[Projects:RegistrationLibrary:RegLib_C04:About| read more about this dataset here]]

=== Download ===
*Data:
**[[Media:RegLib_C04_Data.zip‎|'''Registration Library Case 04: MS Multi-contrast series (PD,T2, T1-GdDTPA): Lesion change assessment''' <small> (Data & Solution Xforms, zip file 18 MB) </small>]]
*Documentation
**[[Media:RegLib_C04_Register_interExam.mov‎|ScreenCast Video: loading data & inter-exam registration: aligning exam 2 to exam 1 <small> (quicktime movie, 8 MB) </small>]]
**[[Media:RegLib_C04_Register_intraExam.mov‎|ScreenCast Video: intra-exam registration: aligning T1Gd of exam 2 to PD of exam 2 <small> (quicktime movie, 8 MB) </small>]]
**[[Media:RegLib_C04_Register_XformHierarchy.mov‎|ScreenCast Video: transform hierarchy: how to arrange the MRML data tree to properly reflect the mutual dependencies of transforms <small> (quicktime movie, 2 MB) </small>]]

=== Keywords ===
MRI, brain, head, intra-subject, multiple sclerosis, MS, multi-contrast, change assessment, dual echo, nested registration

===Input Data===
*reference/fixed : PD.1 baseline exam , 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition, RAS orientation.
*fixed T2.1 baseline exam , 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition, RAS orientation. -> (aligned with PD.1, not used for registering)
*moving: T1.1 (GdDTPA contrast-enhanced scan) baseline exam 0.9375 x 0.9375 x 5 mm voxel size, axial acquisition.
*moving: PD.2 follow-up exam 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition.
*moving: T2.2 follow-up exam 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition. -> same orientation as PD2, will have same transform applied
*moving:T1.2-GdDTPA follow-up exam0.9375 x 0.9375 x 5 mm voxel size, axial acquisition. -> undergoes 2 transforms: first to PD.2, then to PD.1

===Registration Challenges===
*we have multiple nested transforms: each exam is co-registered within itself, and then the exams are aligned to eachother
*potential pathology change can affect the registration
*anisotropic voxel size causes difficulty in rotational alignment
*clipped FOV and low tissue contrast of the post-contrast scan

===Key Strategies===
*we first register the post-contrast scans within each exam to the PD
*second we register the follow-up PD scan to the baseline PD
*we also move the T2 exam within the same Xform
*we then nest the first alignment within the second
*because of the contrast differences and anisotropic resolution we use Mutual Information as cost function for better robustness
=== Procedure ===
*there is a brief movie in the download section that shows this procedure step by step. Guides below use the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)] module, but you may also use the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/AffineRegistration Affine Registration] or [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/ExpertAutomatedRegistration Expert Automated Registration] modules.
*'''Phase 1''': register inter-exam exam 2 -> exam 1
#open the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS) module]
##''Fixed Image Volume'': e1_PD
##''Moving Image Volume'': e2_PD
##Output Settings:
###''Slicer BSpline Transform": none
###''Slicer Linear Transform'': create & rename new transform: Xf1_e21_Affine.tfm
###''Output Image Volume'': none
##''Registration Phases'': check boxes for ''Rigid'' and ''Affine''
##''Main Parameters''
###'''Number of Samples''': 200,000
##click: Apply; runtime < 1 min (MacPro QuadCore 2.4GHz)
#note that the Slicer4.1 version of BRAINS registration does '''not''' automatically place the moving volume inside the result transform, as it did for Slicer 3.6. In order to see the result, you must either go to the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/Data ''Data module''] and drag the moving volume inside the transform node, or select to generate a resampled ''Output Volume'', as done above. The demo movie you can download here shows how to do this.
*'''Phase 2''': register intra-examT1Gd to PD
#open the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS) module]
##''Fixed Image Volume'': e1_PD
##''Moving Image Volume'': e1_T1Gd
##Output Settings:
###''Slicer BSpline Transform": none
###''Slicer Linear Transform'': create & rename new transform: Xf2_e1-T1Gd_Rigid.tfm
###''Output Image Volume'': none
##''Registration Phases'': check boxes for ''Rigid'' only
##''Main Parameters''
###'''Number of Samples''': 200,000
##click: Apply; runtime < 1 min (MacPro QuadCore 2.4GHz)
#note that the Slicer4.1 version of BRAINS registration does '''not''' automatically place the moving volume inside the result transform, as it did for Slicer 3.6. In order to see the result, you must either go to the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/Data ''Data module''] and drag the moving volume inside the transform node, or select to generate a resampled ''Output Volume'', as done above. The demo movie you can download here shows how to do this.
#repeat for exam 2, i.e
##''Fixed Image Volume'': e2_PD
##''Moving Image Volume'': e2_T1Gd
##''Slicer Linear Transform'': create & rename new transform: Xf3_e2-T1Gd_Rigid.tfm
*'''Phase 3''': organize transform hierarchies in the ''Data'' tree
#go to the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/Data ''Data module'']
##drag the volume node e1_T1Gd onto the transform Xf2_e1-T1Gd_Rigid; let go of the mouse button when you see a hilight box appear around the transform node name
##drag the volume node e2_T1Gd onto the transform Xf3_e2-T1Gd_Rigid;
##drag the volume node e2_PD and e2_T2 onto the transform Xf1_e21_Affine.tfm
##drag the transform node Xf3_e2_T1Gd_Rigid.tfm onto the transform Xf1_e21_Affine.tfm
##your MRML data tree should look like the image on the right
##different images into fore- and background, respectively, and use the fade slider to shift between fore- and background to view the registration quality. You can also use OPTION+CMD key and drag the mouse to fade between back- and foreground.
#to apply the transform and lock in the new position, right click on the volume and select ''Harden Transform'' from the popup menu. The node will move back out to the main level. Note that this applies the transform to the physical orientation info in the image header and does not actually perform a resampling. It is recommended to not apply resampling until the very end of an analysis pipeline, to avoid interpolation-related data loss. To perform a resampling follow steps below:
*'''Phase 4''': Resampling (optional)
#go to [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSResample ''Resample Image (BRAINS)'' module] (in the Registration menu)
##''Image To Warp'': e2_PD
##''Reference Image'': e1_PD
##''Output Image'': create new & rename: e2_PD_Xf1
##''Pixel Type'': ushort
##''Warp By Transform'': Xf1_e21_Affine created in Phase I above
##''Interpolation Mode'': '''linear'''
#note to avoid multiple resampling, combine the two nested transforms for the two volumes before performing the resampling step above. Alternatively you can execute the ''Harden Transform'' step above first and then resample the volume after, by giving no transform (i.e. resampling in place) but listing the fixed image (e.g. e1_PD) as reference. This will resample the moving image into the same representation as the reference.
before registration: [[Image:RegLib_C04_DataTree.png|200px|Orig. MRML Data tree]]
after registration: [[Image:RegLib_C04_DataTree2.png|200px|Registered. MRML Data tree: exam 2 is within nested affine transforms]]

=== Registration Results===
[[Image:RegLib_C04_T1Gd-PD_unreg_AnimGif.gif||500px|Unregistered baseline data: PD vs. T1Gd]] Unregistered baseline data: PD vs. T1Gd<br>
[[Image:RegLib_C04_PDunreg_AnimGif.gif||500px|Unregistered followup data: PD exam 2 vs. exam 1]] Unregistered followup data: PD exam 2 vs. exam 1<br>
[[Image:RegLib_C04_T1Gd1-PD1_reg_AnimGif.gif|500px|Registered baseline data]] Registered baseline data <br>
[[Image:RegLib_C04_PDreg_AnimGif.gif|500px|Registered followup data]] Registered followup data<br>
[[Image:RegLib_C04_3DLesionChange_AnimGif.gif|200px|Lesion change visualization in 3D]]Lesion change visualization in 3D<br>
[[Image:RegLib_C04_PDSubtraction.png‎|500px|Lesion change via subtraction imaging of co-registered PD]]Lesion change via subtraction imaging of co-registered PD

Projects:RegistrationLibrary:RegLib C04

2012-06-12T20:07:22Z

Meier: /* Download */

[[Projects:ARRASuplements|Back to ARRA main page]] <br>
[[Projects:RegistrationDocumentation|Back to Registration main page]] <br>
[[Projects:RegistrationDocumentation:UseCaseInventory|Back to Registration Use-case Inventory]] <br>

= <small>v3.6.3</small> [[Image:Slicer_cvers_banner.png|150px]] Slicer Registration Library Case 04: Multi-contrast brain MRI of Multiple Sclerosis =
=== Input ===
{| style="color:#bbbbbb; " cellpadding="10" cellspacing="0" border="0"
|[[Image:Reglib_C04_Thumb_PD1.jpg|100px|lleft|this is the main fixed reference image. All images are ev. aligned into this space]]
|[[Image:Reglib_C04_Thumb_T21.jpg|100px|lleft|this is the main fixed reference image. All images are ev. aligned into this space]]
|[[Image:RegArrow_Affine.png|70px|lleft]]
|[[Image:Reglib_C04_Thumb_Gd1.jpg|100px|lleft|this is the intra-subject moving image. ]]
|-
|exam 1: PD
|exam 1: T2
|
|exam 1: T1-Gd
|-
|[[Image:RegArrow_AffineVert.png|70px|lleft]]
|
|
|
|-
|[[Image:Reglib_C04_Thumb_PD2.jpg|100px|lleft|this is the inter-subject moving image, but also the reference for exam 2]]
|[[Image:Reglib_C04_Thumb_T22.jpg|100px|lleft|this is the inter-subject moving image, but also the reference for exam 2]]
|[[Image:RegArrow_Affine.png|70px|lleft]]
|[[Image:Reglib_C04_Thumb_Gd2.jpg|100px|lleft|this is the moving image. ]]
|-
|exam 2: PD
|exam 2: T2
|
|exam 2: T1-Gd
|}

=== Slicer 4.1 recommended Modules ===
*[http://www.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit BrainsFit]

===Objective / Background ===
This scenario occurs in many forms whenever we wish to assess change in a series of multi-contrast MRI. The follow-up scan(s) are to be aligned with the baseline, but also the different series within each exam need to be co-registered, since the subject may have moved between acquisitions. Hence we have a set of nested registrations. This particular exam features a dual echo scan (PD/T2), where the two structural scans are aligned by default. The post-contrast T1-GdDTPA scan however is not necessarily aligned with the dual echo. Also the post-contrast scan is taken with a clipped field of view (FOV) and a lower axial resolution, with 4mm slices and a 1mm gap (which we treat here as a de facto 5mm slice).
[[Projects:RegistrationLibrary:RegLib_C04:About| read more about this dataset here]]

=== Download ===
*Data:
**[[Media:RegLib_C04_Data.zip‎|'''Registration Library Case 04: MS Multi-contrast series (PD,T2, T1-GdDTPA): Lesion change assessment''' <small> (Data & Solution Xforms, zip file 18 MB) </small>]]
*Documentation
**[[Media:RegLib_C04_Register_interExam.mov‎|ScreenCast Video: loading data & inter-exam registration: aligning exam 2 to exam 1 <small> (quicktime movie, 8 MB) </small>]]
**[[Media:RegLib_C04_Register_intraExam.mov‎|ScreenCast Video: intra-exam registration: aligning T1Gd of exam 2 to PD of exam 2 <small> (quicktime movie, 8 MB) </small>]]
**[[Media:RegLib_C04_Register_XformHierarchy.mov‎|ScreenCast Video: transform hierarchy: how to arrange the MRML data tree to properly reflect the mutual dependencies of transforms <small> (quicktime movie, 2 MB) </small>]]

=== Keywords ===
MRI, brain, head, intra-subject, multiple sclerosis, MS, multi-contrast, change assessment, dual echo, nested registration

===Input Data===
*reference/fixed : PD.1 baseline exam , 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition, RAS orientation.
*fixed T2.1 baseline exam , 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition, RAS orientation. -> (aligned with PD.1, not used for registering)
*moving: T1.1 (GdDTPA contrast-enhanced scan) baseline exam 0.9375 x 0.9375 x 5 mm voxel size, axial acquisition.
*moving: PD.2 follow-up exam 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition.
*moving: T2.2 follow-up exam 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition. -> same orientation as PD2, will have same transform applied
*moving:T1.2-GdDTPA follow-up exam0.9375 x 0.9375 x 5 mm voxel size, axial acquisition. -> undergoes 2 transforms: first to PD.2, then to PD.1

===Registration Challenges===
*we have multiple nested transforms: each exam is co-registered within itself, and then the exams are aligned to eachother
*potential pathology change can affect the registration
*anisotropic voxel size causes difficulty in rotational alignment
*clipped FOV and low tissue contrast of the post-contrast scan

===Key Strategies===
*we first register the post-contrast scans within each exam to the PD
*second we register the follow-up PD scan to the baseline PD
*we also move the T2 exam within the same Xform
*we then nest the first alignment within the second
*because of the contrast differences and anisotropic resolution we use Mutual Information as cost function for better robustness
=== Procedure ===
*there is a brief movie in the download section that shows this procedure step by step. Guides below use the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)] module, but you may also use the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/AffineRegistration Affine Registration or [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/ExpertAutomatedRegistration Expert Automated Registration] modules.
*'''Phase 1''': register inter-exam exam 2 -> exam 1
#open the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS) module]
##''Fixed Image Volume'': e1_PD
##''Moving Image Volume'': e2_PD
##Output Settings:
###''Slicer BSpline Transform": none
###''Slicer Linear Transform'': create & rename new transform: Xf1_e21_Affine.tfm
###''Output Image Volume'': none
##''Registration Phases'': check boxes for ''Rigid'' and ''Affine''
##''Main Parameters''
###'''Number of Samples''': 200,000
##click: Apply; runtime < 1 min (MacPro QuadCore 2.4GHz)
#note that the Slicer4.1 version of BRAINS registration does '''not''' automatically place the moving volume inside the result transform, as it did for Slicer 3.6. In order to see the result, you must either go to the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/Data ''Data module''] and drag the moving volume inside the transform node, or select to generate a resampled ''Output Volume'', as done above. The demo movie you can download here shows how to do this.
*'''Phase 2''': register intra-examT1Gd to PD
#open the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS) module]
##''Fixed Image Volume'': e1_PD
##''Moving Image Volume'': e1_T1Gd
##Output Settings:
###''Slicer BSpline Transform": none
###''Slicer Linear Transform'': create & rename new transform: Xf2_e1-T1Gd_Rigid.tfm
###''Output Image Volume'': none
##''Registration Phases'': check boxes for ''Rigid'' only
##''Main Parameters''
###'''Number of Samples''': 200,000
##click: Apply; runtime < 1 min (MacPro QuadCore 2.4GHz)
#note that the Slicer4.1 version of BRAINS registration does '''not''' automatically place the moving volume inside the result transform, as it did for Slicer 3.6. In order to see the result, you must either go to the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/Data ''Data module''] and drag the moving volume inside the transform node, or select to generate a resampled ''Output Volume'', as done above. The demo movie you can download here shows how to do this.
#repeat for exam 2, i.e
##''Fixed Image Volume'': e2_PD
##''Moving Image Volume'': e2_T1Gd
##''Slicer Linear Transform'': create & rename new transform: Xf3_e2-T1Gd_Rigid.tfm
*'''Phase 3''': organize transform hierarchies in the ''Data'' tree
#go to the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/Data ''Data module'']
##drag the volume node e1_T1Gd onto the transform Xf2_e1-T1Gd_Rigid; let go of the mouse button when you see a hilight box appear around the transform node name
##drag the volume node e2_T1Gd onto the transform Xf3_e2-T1Gd_Rigid;
##drag the volume node e2_PD and e2_T2 onto the transform Xf1_e21_Affine.tfm
##drag the transform node Xf3_e2_T1Gd_Rigid.tfm onto the transform Xf1_e21_Affine.tfm
##your MRML data tree should look like the image on the right
##different images into fore- and background, respectively, and use the fade slider to shift between fore- and background to view the registration quality. You can also use OPTION+CMD key and drag the mouse to fade between back- and foreground.
#to apply the transform and lock in the new position, right click on the volume and select ''Harden Transform'' from the popup menu. The node will move back out to the main level. Note that this applies the transform to the physical orientation info in the image header and does not actually perform a resampling. It is recommended to not apply resampling until the very end of an analysis pipeline, to avoid interpolation-related data loss. To perform a resampling follow steps below:
*'''Phase 4''': Resampling (optional)
#go to [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSResample ''Resample Image (BRAINS)'' module] (in the Registration menu)
##''Image To Warp'': e2_PD
##''Reference Image'': e1_PD
##''Output Image'': create new & rename: e2_PD_Xf1
##''Pixel Type'': ushort
##''Warp By Transform'': Xf1_e21_Affine created in Phase I above
##''Interpolation Mode'': '''linear'''
#note to avoid multiple resampling, combine the two nested transforms for the two volumes before performing the resampling step above. Alternatively you can execute the ''Harden Transform'' step above first and then resample the volume after, by giving no transform (i.e. resampling in place) but listing the fixed image (e.g. e1_PD) as reference. This will resample the moving image into the same representation as the reference.
before registration: [[Image:RegLib_C04_DataTree.png|200px|Orig. MRML Data tree]]
after registration: [[Image:RegLib_C04_DataTree2.png|200px|Registered. MRML Data tree: exam 2 is within nested affine transforms]]

=== Registration Results===
[[Image:RegLib_C04_T1Gd-PD_unreg_AnimGif.gif||500px|Unregistered baseline data: PD vs. T1Gd]] Unregistered baseline data: PD vs. T1Gd<br>
[[Image:RegLib_C04_PDunreg_AnimGif.gif||500px|Unregistered followup data: PD exam 2 vs. exam 1]] Unregistered followup data: PD exam 2 vs. exam 1<br>
[[Image:RegLib_C04_T1Gd1-PD1_reg_AnimGif.gif|500px|Registered baseline data]] Registered baseline data <br>
[[Image:RegLib_C04_PDreg_AnimGif.gif|500px|Registered followup data]] Registered followup data<br>
[[Image:RegLib_C04_3DLesionChange_AnimGif.gif|200px|Lesion change visualization in 3D]]Lesion change visualization in 3D<br>
[[Image:RegLib_C04_PDSubtraction.png‎|500px|Lesion change via subtraction imaging of co-registered PD]]Lesion change via subtraction imaging of co-registered PD

Projects:RegistrationLibrary:RegLib C04

2012-06-12T20:06:30Z

Meier: /* Download */

[[Projects:ARRASuplements|Back to ARRA main page]] <br>
[[Projects:RegistrationDocumentation|Back to Registration main page]] <br>
[[Projects:RegistrationDocumentation:UseCaseInventory|Back to Registration Use-case Inventory]] <br>

= <small>v3.6.3</small> [[Image:Slicer_cvers_banner.png|150px]] Slicer Registration Library Case 04: Multi-contrast brain MRI of Multiple Sclerosis =
=== Input ===
{| style="color:#bbbbbb; " cellpadding="10" cellspacing="0" border="0"
|[[Image:Reglib_C04_Thumb_PD1.jpg|100px|lleft|this is the main fixed reference image. All images are ev. aligned into this space]]
|[[Image:Reglib_C04_Thumb_T21.jpg|100px|lleft|this is the main fixed reference image. All images are ev. aligned into this space]]
|[[Image:RegArrow_Affine.png|70px|lleft]]
|[[Image:Reglib_C04_Thumb_Gd1.jpg|100px|lleft|this is the intra-subject moving image. ]]
|-
|exam 1: PD
|exam 1: T2
|
|exam 1: T1-Gd
|-
|[[Image:RegArrow_AffineVert.png|70px|lleft]]
|
|
|
|-
|[[Image:Reglib_C04_Thumb_PD2.jpg|100px|lleft|this is the inter-subject moving image, but also the reference for exam 2]]
|[[Image:Reglib_C04_Thumb_T22.jpg|100px|lleft|this is the inter-subject moving image, but also the reference for exam 2]]
|[[Image:RegArrow_Affine.png|70px|lleft]]
|[[Image:Reglib_C04_Thumb_Gd2.jpg|100px|lleft|this is the moving image. ]]
|-
|exam 2: PD
|exam 2: T2
|
|exam 2: T1-Gd
|}

=== Slicer 4.1 recommended Modules ===
*[http://www.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit BrainsFit]

===Objective / Background ===
This scenario occurs in many forms whenever we wish to assess change in a series of multi-contrast MRI. The follow-up scan(s) are to be aligned with the baseline, but also the different series within each exam need to be co-registered, since the subject may have moved between acquisitions. Hence we have a set of nested registrations. This particular exam features a dual echo scan (PD/T2), where the two structural scans are aligned by default. The post-contrast T1-GdDTPA scan however is not necessarily aligned with the dual echo. Also the post-contrast scan is taken with a clipped field of view (FOV) and a lower axial resolution, with 4mm slices and a 1mm gap (which we treat here as a de facto 5mm slice).
[[Projects:RegistrationLibrary:RegLib_C04:About| read more about this dataset here]]

=== Download ===
*Data:
**[[Media:RegLib_C04_Data.zip‎|'''Registration Library Case 04: MS Multi-contrast series (PD,T2, T1-GdDTPA): Lesion change assessment''' <small> (Data & Solution Xforms, zip file 18 MB) </small>]]
*Documentation
**[[Media:RegLib_C04_Register_interExam.mov‎|ScreenCast Video: inter-exam registration: aligning exam 2 to exam 1 <small> (quicktime movie, 8 MB) </small>]]
**[[Media:RegLib_C04_Register_interExam.mov‎|ScreenCast Video: intra-exam registration: aligning T1Gd of exam 2 to PD of exam 2 <small> (quicktime movie, 8 MB) </small>]]
**[[Media:RegLib_C04_Register_interExam.mov‎|ScreenCast Video: transform hierarchy: how to arrange the MRML data tree to properly reflect the mutual dependencies of transforms <small> (quicktime movie, 2 MB) </small>]]

=== Keywords ===
MRI, brain, head, intra-subject, multiple sclerosis, MS, multi-contrast, change assessment, dual echo, nested registration

===Input Data===
*reference/fixed : PD.1 baseline exam , 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition, RAS orientation.
*fixed T2.1 baseline exam , 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition, RAS orientation. -> (aligned with PD.1, not used for registering)
*moving: T1.1 (GdDTPA contrast-enhanced scan) baseline exam 0.9375 x 0.9375 x 5 mm voxel size, axial acquisition.
*moving: PD.2 follow-up exam 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition.
*moving: T2.2 follow-up exam 0.9375 x 0.9375 x 3 mm voxel size, axial acquisition. -> same orientation as PD2, will have same transform applied
*moving:T1.2-GdDTPA follow-up exam0.9375 x 0.9375 x 5 mm voxel size, axial acquisition. -> undergoes 2 transforms: first to PD.2, then to PD.1

===Registration Challenges===
*we have multiple nested transforms: each exam is co-registered within itself, and then the exams are aligned to eachother
*potential pathology change can affect the registration
*anisotropic voxel size causes difficulty in rotational alignment
*clipped FOV and low tissue contrast of the post-contrast scan

===Key Strategies===
*we first register the post-contrast scans within each exam to the PD
*second we register the follow-up PD scan to the baseline PD
*we also move the T2 exam within the same Xform
*we then nest the first alignment within the second
*because of the contrast differences and anisotropic resolution we use Mutual Information as cost function for better robustness
=== Procedure ===
*there is a brief movie in the download section that shows this procedure step by step. Guides below use the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS)] module, but you may also use the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/AffineRegistration Affine Registration or [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/ExpertAutomatedRegistration Expert Automated Registration] modules.
*'''Phase 1''': register inter-exam exam 2 -> exam 1
#open the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS) module]
##''Fixed Image Volume'': e1_PD
##''Moving Image Volume'': e2_PD
##Output Settings:
###''Slicer BSpline Transform": none
###''Slicer Linear Transform'': create & rename new transform: Xf1_e21_Affine.tfm
###''Output Image Volume'': none
##''Registration Phases'': check boxes for ''Rigid'' and ''Affine''
##''Main Parameters''
###'''Number of Samples''': 200,000
##click: Apply; runtime < 1 min (MacPro QuadCore 2.4GHz)
#note that the Slicer4.1 version of BRAINS registration does '''not''' automatically place the moving volume inside the result transform, as it did for Slicer 3.6. In order to see the result, you must either go to the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/Data ''Data module''] and drag the moving volume inside the transform node, or select to generate a resampled ''Output Volume'', as done above. The demo movie you can download here shows how to do this.
*'''Phase 2''': register intra-examT1Gd to PD
#open the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSFit General Registration (BRAINS) module]
##''Fixed Image Volume'': e1_PD
##''Moving Image Volume'': e1_T1Gd
##Output Settings:
###''Slicer BSpline Transform": none
###''Slicer Linear Transform'': create & rename new transform: Xf2_e1-T1Gd_Rigid.tfm
###''Output Image Volume'': none
##''Registration Phases'': check boxes for ''Rigid'' only
##''Main Parameters''
###'''Number of Samples''': 200,000
##click: Apply; runtime < 1 min (MacPro QuadCore 2.4GHz)
#note that the Slicer4.1 version of BRAINS registration does '''not''' automatically place the moving volume inside the result transform, as it did for Slicer 3.6. In order to see the result, you must either go to the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/Data ''Data module''] and drag the moving volume inside the transform node, or select to generate a resampled ''Output Volume'', as done above. The demo movie you can download here shows how to do this.
#repeat for exam 2, i.e
##''Fixed Image Volume'': e2_PD
##''Moving Image Volume'': e2_T1Gd
##''Slicer Linear Transform'': create & rename new transform: Xf3_e2-T1Gd_Rigid.tfm
*'''Phase 3''': organize transform hierarchies in the ''Data'' tree
#go to the [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/Data ''Data module'']
##drag the volume node e1_T1Gd onto the transform Xf2_e1-T1Gd_Rigid; let go of the mouse button when you see a hilight box appear around the transform node name
##drag the volume node e2_T1Gd onto the transform Xf3_e2-T1Gd_Rigid;
##drag the volume node e2_PD and e2_T2 onto the transform Xf1_e21_Affine.tfm
##drag the transform node Xf3_e2_T1Gd_Rigid.tfm onto the transform Xf1_e21_Affine.tfm
##your MRML data tree should look like the image on the right
##different images into fore- and background, respectively, and use the fade slider to shift between fore- and background to view the registration quality. You can also use OPTION+CMD key and drag the mouse to fade between back- and foreground.
#to apply the transform and lock in the new position, right click on the volume and select ''Harden Transform'' from the popup menu. The node will move back out to the main level. Note that this applies the transform to the physical orientation info in the image header and does not actually perform a resampling. It is recommended to not apply resampling until the very end of an analysis pipeline, to avoid interpolation-related data loss. To perform a resampling follow steps below:
*'''Phase 4''': Resampling (optional)
#go to [http://wiki.slicer.org/slicerWiki/index.php/Documentation/4.1/Modules/BRAINSResample ''Resample Image (BRAINS)'' module] (in the Registration menu)
##''Image To Warp'': e2_PD
##''Reference Image'': e1_PD
##''Output Image'': create new & rename: e2_PD_Xf1
##''Pixel Type'': ushort
##''Warp By Transform'': Xf1_e21_Affine created in Phase I above
##''Interpolation Mode'': '''linear'''
#note to avoid multiple resampling, combine the two nested transforms for the two volumes before performing the resampling step above. Alternatively you can execute the ''Harden Transform'' step above first and then resample the volume after, by giving no transform (i.e. resampling in place) but listing the fixed image (e.g. e1_PD) as reference. This will resample the moving image into the same representation as the reference.
before registration: [[Image:RegLib_C04_DataTree.png|200px|Orig. MRML Data tree]]
after registration: [[Image:RegLib_C04_DataTree2.png|200px|Registered. MRML Data tree: exam 2 is within nested affine transforms]]

=== Registration Results===
[[Image:RegLib_C04_T1Gd-PD_unreg_AnimGif.gif||500px|Unregistered baseline data: PD vs. T1Gd]] Unregistered baseline data: PD vs. T1Gd<br>
[[Image:RegLib_C04_PDunreg_AnimGif.gif||500px|Unregistered followup data: PD exam 2 vs. exam 1]] Unregistered followup data: PD exam 2 vs. exam 1<br>
[[Image:RegLib_C04_T1Gd1-PD1_reg_AnimGif.gif|500px|Registered baseline data]] Registered baseline data <br>
[[Image:RegLib_C04_PDreg_AnimGif.gif|500px|Registered followup data]] Registered followup data<br>
[[Image:RegLib_C04_3DLesionChange_AnimGif.gif|200px|Lesion change visualization in 3D]]Lesion change visualization in 3D<br>
[[Image:RegLib_C04_PDSubtraction.png‎|500px|Lesion change via subtraction imaging of co-registered PD]]Lesion change via subtraction imaging of co-registered PD